Conference Papers

Upcoming ML/AI and Finance conference calendar, plus topic clustering and research trends from peer-reviewed papers.

Total: 55,512 papers analyzed
📅

Conference Calendar

18 events
Past Conferences (35 events) +
2025 (17 events) +
ML/AI A*
NeurIPS
Neural Information Processing Systems
Dec 8-14, 2025 San Diego, USA
~3,500 papers
Finance A
ICAIF
ACM International Conference on AI in Finance
Nov 13-16, 2025 TBD
~100 papers
ML/AI A*
EMNLP
Empirical Methods in Natural Language Processing
Nov 5-9, 2025 Suzhou, China
~1,100 papers
ML/AI A*
CoRL
Conference on Robot Learning
Nov 4-7, 2025 Seoul, South Korea
~450 papers
ML/AI A*
ICCV
International Conference on Computer Vision
Oct 19-25, 2025 Honolulu, USA
~2,100 papers
ML/AI A
InterSpeech
Conference on Speech Communication
Aug 27-31, 2025 Rotterdam, Netherlands
~1,600 papers
Monetary A*
Jackson Hole
Jackson Hole Economic Symposium
Aug 21-23, 2025 Jackson Hole, USA
~20 papers
ML/AI A*
ACL
Association for Computational Linguistics
Jul 27 - Aug 01, 2025 Vienna, Austria
~1,200 papers
ML/AI A*
SIGIR
Research on Information Retrieval
Jul 20-24, 2025 Padua, Italy
~400 papers
ML/AI A*
ICML
International Conference on Machine Learning
Jul 13-19, 2025 Vancouver, Canada
~2,600 papers
ML/AI A
RSS
Robotics: Science and Systems
Jun 21-25, 2025 Los Angeles, USA
~200 papers
ML/AI A*
CVPR
Computer Vision and Pattern Recognition
Jun 10-17, 2025 Nashville, USA
~2,700 papers
ML/AI A*
NAACL
North American Chapter of ACL
Apr 29 - May 04, 2025 Albuquerque, USA
~700 papers
ML/AI A*
ICLR
International Conference on Learning Representations
Apr 24-28, 2025 Singapore
~2,400 papers
ML/AI A
EACL
European Chapter of ACL
Mar 30 - Apr 04, 2025 Dubrovnik, Croatia
~400 papers
ML/AI A*
AAAI
AAAI Conference on Artificial Intelligence
Feb 25 - Mar 04, 2025 Philadelphia, USA
~2,300 papers
Finance A*
AFA
American Finance Association Annual Meeting
Jan 3-5, 2025 San Francisco, USA
~400 papers
2024 (17 events) +
ML/AI A*
NeurIPS
Neural Information Processing Systems
Dec 9-15, 2024 Vancouver, Canada
~3,500 papers
Finance A
ICAIF
ACM International Conference on AI in Finance
Nov 14-17, 2024 Brooklyn, USA
~100 papers
ML/AI A*
EMNLP
Empirical Methods in Natural Language Processing
Nov 12-16, 2024 Miami, USA
~1,100 papers
ML/AI A*
CoRL
Conference on Robot Learning
Nov 6-9, 2024 Munich, Germany
~450 papers
ML/AI A*
ECCV
European Conference on Computer Vision
Sep 29 - Oct 04, 2024 Milan, Italy
~1,600 papers
ML/AI A
InterSpeech
Conference on Speech Communication
Sep 1-5, 2024 Kos, Greece
~1,600 papers
Monetary A*
Jackson Hole
Jackson Hole Economic Symposium
Aug 22-24, 2024 Jackson Hole, USA
~20 papers
ML/AI A*
ACL
Association for Computational Linguistics
Aug 11-16, 2024 Bangkok, Thailand
~1,200 papers
ML/AI A*
ICML
International Conference on Machine Learning
Jul 21-27, 2024 Vienna, Austria
~2,600 papers
ML/AI A
RSS
Robotics: Science and Systems
Jul 15-19, 2024 Delft, Netherlands
~200 papers
ML/AI A*
SIGIR
Research on Information Retrieval
Jul 14-18, 2024 Washington DC, USA
~400 papers
ML/AI A*
CVPR
Computer Vision and Pattern Recognition
Jun 17-21, 2024 Seattle, USA
~2,700 papers
ML/AI A*
NAACL
North American Chapter of ACL
Jun 16-21, 2024 Mexico City, Mexico
~700 papers
ML/AI A*
ICLR
International Conference on Learning Representations
May 7-11, 2024 Vienna, Austria
~2,400 papers
ML/AI A
EACL
European Chapter of ACL
Mar 17-22, 2024 Malta
~400 papers
ML/AI A*
AAAI
AAAI Conference on Artificial Intelligence
Feb 20-27, 2024 Vancouver, Canada
~2,300 papers
Finance A*
AFA
American Finance Association Annual Meeting
Jan 5-7, 2024 San Antonio, USA
~400 papers

Paper Analysis by Venue

ACL 2025

Association for Computational Linguistics 4,729 papers
+
Language Model Evaluation 393
Assessing and evaluating language models beyond traditional benchmarks focusing on bias and robustness in diverse contexts.
evaluation metrics (1)
Sub-topics:
Benchmarking LLM Performance (133)
Error Correction Techniques (70)
Bias Evaluation Methods (52)
Retrieval-Augmented Generation (44)
Dynamic Response Sampling (36)
Human-in-the-Loop Evaluation (34)
Fine-Grained Multimodal Reasoning 199
Techniques for enhancing reasoning capabilities across various data modalities at the sentence level.
sentence-level optimizationadaptive algorithmsmultimodal interactionspreference modeling
Sub-topics:
Contextual Comprehension Frameworks (67)
Adaptive Multimodal Retrieval Techniques (45)
Multimodal Knowledge Integration (36)
Bias Mitigation in Multimodal Learning (21)
Multi-Agent Collaborative Reasoning (15)
Fine-Grained Emotion Recognition (15)
Automated Communication Skills Assessment 62
Automating the scoring system to evaluate communication skills in healthcare settings, focusing on performance and scalability.
physician-patient interactioncommunication scoringclinical assessmentsnatural language processing
Multimodal Emotion Recognition 60
Research focused on bridging gaps in human-annotated datasets for emotion recognition in multiple languages.
emotion classification (1)
Contextual Document Retrieval 52
Improving retrieval techniques using context-aware methods to enhance document access and relevance.
context-aware alignmentdocument retrieval techniquesLLM generationknowledge graphs
Bias in Political Decision-Making 42
Analyzing how biases within language models can impact political decisions and public discourse.
language model biasinfluence on politicsethical implicationsdecision-making analysis
Commonsense Reasoning in Language Models 38
Exploration and benchmarking of commonsense reasoning abilities within large language models for complex tasks.
commonsense knowledge (1)large language models (3)
Adaptive Quantization Techniques 29
Developing adaptive quantization techniques to improve performance and efficiency in AI model inference.
quantization strategiesoutlier detectionresource-efficient modelsfloating-point representation
Hate Speech Detection 25
Investigating advanced methods for detecting and analyzing hate speech and harassment in online platforms.
transphobic hate (1)

AFA 2025

American Finance Association Annual Meeting 83 papers
+
Long-Term Behavioral Finance 14
Examining how historical socio-political events influence long-standing attitudes toward investment practices and financial market participation.
attitudes (1)financial markets (1)
FinTech Credit Impact 14
Investigating how the adoption of cashless payment methods influences borrowers' access to capital and risk profiles in FinTech lending.
FinTech lending (1)cashless payments (1)
Internal Organization Post-IPO 12
Examining organizational transformations within firms following their transition to public ownership through IPOs.
initial public offerings (1)
Corporate Social Impact Measurement 10
Conceptualizing and quantifying social impact in corporate contexts and its implications for stakeholder engagement.
impact investing (1)stakeholder capitalism (1)social impact (1)
Debt Discharge Effects 10
Evaluating the impact of random debt discharge episodes on the financial behavior and outcomes of student borrowers.
student debt relief (1)borrower outcomes (1)
Supply Chain Uncertainty Analysis 8
Analyzing the effects of uncertainty shocks within supply chains on firm-level economic decisions and production strategies.
upstream uncertainty (1)downstream uncertainty (1)economic activity (1)
Loan Covenant Evolution 8
Analyzing the decline in loan covenant violations among public firms and the factors influencing covenant design.
covenant violations (1)public firms (2)covenant design (1)
Portfolio Choice Dynamics 5
Studying the influence of risk preferences and behavioral frictions on investors' portfolio choices in retirement accounts.
portfolio choice (1)risk preferences (1)
ESG Impact on Firm Valuation 5
Assessing how negative ESG news affects analysts' valuation forecasts and the consequent implications for firm value.
environmental governancesocial impactfirm valueanalyst forecasts
Social Media Sentiment Analysis 2
Investigating the correlation between social media sentiment and corporate merger withdrawal decisions.
merger withdrawalssocial mediasentiment trackingpredictive modeling

CVPR 2025

Computer Vision and Pattern Recognition 2,881 papers
+
3D Reconstruction Methods 175
Focuses on techniques for reconstructing 3D models and scenes from various data inputs, including images and LiDAR data.
LiDAR segmentation (1)camera pose (1)
Sub-topics:
3D Scene Understanding (79)
Sparse Representation for 3D (39)
3D Object Detection (27)
3D Gaussian Splatting (11)
Multi-view Reconstruction (11)
Monocular 3D Reconstruction (8)
Diffusion Model Architectures 164
Research focuses on the development and refinement of diffusion models for tasks such as image generation, compression, and perception.
image generation (4)region adaptive (1)
Sub-topics:
3D Object Generation (52)
Post-Training Optimization (42)
Adaptive Sampling Techniques (30)
Semantic Understanding in Diffusion (20)
Contrastive Learning Approaches (19)
Multimodal Learning Techniques 136
Explores methods for integrating and understanding data across multiple modalities to enhance learning outcomes.
text-image integrationaudio-visual perceptionmultimodal retrievalgesture generation
Sub-topics:
Multimodal Fusion Techniques (41)
Adaptive Learning Strategies (35)
Multimodal Data Generation (30)
Multimodal Interaction Analysis (12)
Cross-Modal Alignment (10)
Benchmarking Multimodal Models (8)
Geometric and Spatial Reasoning 94
Focuses on mechanisms to leverage geometric and spatial information for refined reasoning in visual and multimodal contexts.
spatial-temporal reasoning (1)
Incremental Learning Strategies 92
Develops methodologies for learning new information sequentially while retaining previously acquired knowledge efficiently.
class-incremental learning (2)continual learning (2)
Data Distillation Methods 71
Investigates techniques for improving the efficiency and effectiveness of training sets through selective refinement and distillation.
non-critical region (1)
Zero-Shot Learning and Attribution 68
Investigates strategies for model performance in recognizing and attributing data in unseen scenarios without explicit training.
source attribution (1)anomaly detection (2)
Motion and Pose Estimation 63
Focusing on methods for accurately estimating motion and pose in various contexts, especially from the user's perspective.
egocentric vision (1)
Natural Language Alignment Techniques 54
Studies methods for aligning textual instructions and outputs with corresponding visual or motion-related tasks.
text-to-motioninstruction tuningGPT alignmentevent-level coordination
Graph-Based Learning Approaches 47
Explores the use of graph structures for learning tasks, particularly in scenarios with privacy considerations and distributed data.
federated learning (5)graph neural networks (1)homophily heterogeneity (1)

EMNLP 2025

Empirical Methods in Natural Language Processing 4,361 papers
+
Text Generation Task Analysis 156
Analyzing and improving techniques for generating coherent and creative text outputs in various contexts.
story generation (1)pun generation (1)
Sub-topics:
Evaluation Frameworks for Text Generation (58)
Adaptive Prompting Techniques (25)
Bias and Fairness in LLMs (20)
Multi-agent Collaboration for Text Generation (18)
Cognitive Models in Language Production (18)
Improving Consistency in Generated Text (17)
Prompt Engineering Optimization 122
Investigations into the design and optimization of prompts for enhancing language model outputs.
language models (20)
Sub-topics:
Evaluation Frameworks for Prompting (53)
Prompt Optimization Techniques (23)
Contextual Prompt Adjustments (21)
Guidelines for Multimodal Prompts (17)
Adaptive Prompt Strategies (7)
Cultural Knowledge Representation 122
Studies aimed at incorporating and representing cultural and religious knowledge within language models.
cultural questionsreligious knowledgedata augmentationtaxonomy-guided frameworks
Sub-topics:
Culturally-Aware Natural Language Processing (54)
Multilingual Knowledge Representation (27)
Cultural Bias in AI Systems (24)
Cross-Cultural Evaluation Metrics (12)
Representation of Cultural Narratives (4)
Multimodal Model Alignment 108
Researching techniques for aligning information and representation in multimodal models integrating various data types.
multimodal learningalignment techniquesvisual-language modelscontextual knowledge
Sub-topics:
Evaluation Metrics for Alignment (52)
Culturally-aware Multimodal Models (15)
Adaptive Fusion Strategies (15)
Symmetric Multimodal Alignment (10)
Neuro-Symbolic Techniques in Alignment (9)
Interdisciplinary Recommender Systems (7)
Dialog Systems and Education 100
Developments in utilizing dialog systems to enhance educational experiences and assess pedagogic effectiveness.
conversational agents (1)
Sub-topics:
Automated Student Assessment Systems (38)
Benchmarking Educational Dialogue Systems (18)
Multimodal Learning Environments (13)
Cultural Adaptation in Educational Dialogs (13)
Prompt Engineering for Educational Dialogs (9)
Explainable Chatbot Interactions (9)
Safety and Ethical AI 87
Research focused on the evaluation and enhancement of safety measures and ethical governance in AI implementations.
safety benchmarkingethical considerationsAI governancelanguage model assessment
Evaluation of Mathematical Reasoning 83
Exploring how models perform on mathematical reasoning tasks and the evaluation of their solution strategies.
math problemsabstract reasoningcorrect solutionslanguage model evaluation
Bias Mitigation in Language Models 78
Efforts to identify and reduce biases within language models through various analytical and augmentation strategies.
bias analysis (1)
Reinforcement Learning Techniques 55
Development and evaluation of reinforcement learning methods for improving model performance across various tasks.
reinforcement learning (5)posterior sampling (1)
Continual Learning Evaluation 47
Research focused on frameworks to evaluate and improve continual learning capabilities in language models.
continual learning (1)language models (3)

ICCV 2025

International Conference on Computer Vision 2,701 papers
+
3D Scene Reconstruction 165
Approaches for effective modeling and reconstruction of 3D scenes, including handling dynamic elements and camera motion.
Gaussian splatting (11)
Sub-topics:
Multi-View Scene Understanding (46)
Depth Estimation Techniques (32)
Object-Aware 3D Modeling (30)
3D Gaussian Splatting (22)
Monocular 3D Reconstruction (20)
Diffusion Model Enhancements 155
Advancements in diffusion models addressing uncertainty, generative capabilities, and applications in various domains.
asymmetric learning (1)epistemic uncertainty (1)image generation (7)
Sub-topics:
Domain Adaptation Strategies (43)
Amodal Reconstruction Methods (37)
Guided Diffusion Frameworks (22)
Temporal Consistency in Diffusion (21)
Adaptive Sampling Techniques (18)
Diffusion Model Evaluation Metrics (13)
Image Segmentation Methods 155
Techniques enhancing image segmentation models for improved accuracy and applicability across varied datasets and conditions.
semantic segmentation (8)pansharpening (1)segmentation models (1)
Sub-topics:
Multi-Modal Image Segmentation (46)
Gaussian Splatting for Segmentation (36)
Few-Shot Image Segmentation (34)
Temporal Segmentation in Video (21)
Adaptive Medical Image Segmentation (17)
Video Generation Techniques 131
Innovative methods for generating and manipulating video content, focusing on efficiency and quality.
video synthesis (1)distillation (3)motion generation (1)context perception (1)
Sub-topics:
Adaptive Video Processing (55)
3D Scene Generation (36)
Diffusion-based Video Synthesis (19)
Motion Reasoning and Generation (15)
Video Prediction Models (5)
Vision-Language Integration 102
Research emphasizing the synergistic interaction between vision and language for tasks like object retrieval and scene understanding.
CLIP modelsopen-set retrievalchain-of-affordancecontextual representation
Sub-topics:
3D Scene Understanding (26)
Adaptive Representation Learning (25)
Cross-Modal Interaction Learning (25)
Evaluation Benchmarks for Vision-Language Models (11)
Temporal Alignment in Multi-Modal Generation (8)
Visual Question Answering (7)
Event-based Vision 65
Exploration of adapting image detection models to leverage the unique characteristics of event-based vision systems.
latent space adaptation (1)image detectors (1)dynamic scenes (1)
Unsupervised Anomaly Detection 61
Strategies for identifying anomalies in data through unsupervised mechanisms that leverage structural and behavioral insights.
trace guidancevelocity alignmenttop-down distillationunsupervised learning
Quantization & Model Compression 51
Methods for reducing the resource footprint of machine learning models while maintaining accuracy and performance.
post-training quantization (1)
Federated Learning 45
Techniques for preserving privacy and improving generalizability in federated learning environments through innovative model architectures.
federated meta-learning (1)collaborative learning (1)
Next-X Prediction 41
Research focusing on extending next-token predictive models to multi-step predictions in visual generation tasks.
autoregressive generationvisual generationmulti-step predictionpredictive modeling

ICML 2025

International Conference on Machine Learning 3,380 papers
+
Unsupervised Learning Techniques 570
This area examines methodologies for learning patterns and representations in data without label supervision or explicit guidance.
pseudo-labeling (1)imitation learning (1)
Sub-topics:
Causal Discovery Methods (115)
Self-Supervised Learning (114)
Generative Models (112)
Clustering Algorithms (76)
Dimensionality Reduction Techniques (54)
Graph-Based Unsupervised Learning (38)
Generative Modeling Techniques 456
This area focuses on developing generative models capable of producing high-quality data samples through various training methods.
deep generative models (1)mixture distributions (1)
Sub-topics:
Generative Modeling Evaluation Metrics (154)
Generative Flow Models (142)
Latent Space Optimization (39)
Multimodal Generative Synthesis (30)
Conditional Generative Models (29)
Generative Adversarial Networks (GANs) (25)
Natural Language Processing Techniques 390
This domain investigates specific methodologies for understanding and generating human language, including tokenization and parsing techniques.
language modeling (2)
Sub-topics:
Transfer Learning in NLP (111)
Evaluation of Language Models (76)
Text Generation Models (62)
Fairness in Language Models (48)
Multimodal Language Processing (42)
Knowledge Distillation in NLP (26)
Reinforcement Learning from Feedback 344
This topic focuses on enhancing reinforcement learning through feedback-driven methods, including safety mechanisms and multi-objective optimizations.
RLHF (5)multi-objective (6)
Sub-topics:
Sample Efficiency in RL (199)
Feedback Integration Techniques (74)
Exploration Strategies in RL (18)
Multi-task Reinforcement Learning (17)
Safe Reinforcement Learning (14)
Interactive Reinforcement Learning (9)
Large Language Model Alignment 303
This topic centers around aligning large language models with human-like reasoning, safety metrics, and task-specific requirements.
safety alignment (1)fine-tuning (11)multimodal LLMs (2)large language models (35)
Sub-topics:
Task Generalization Techniques (81)
Robustness to Distribution Shift (63)
Evaluating Alignment in Context (46)
Fine-tuning Strategies (44)
Multimodal Learning Approaches (26)
Interpretable Alignment Metrics (24)
Graph Neural Networks 256
This area investigates the application and adaptation of graph models and spectral techniques for processing and learning from graph-structured data.
node representation (1)
Sub-topics:
Graph Neural Network Generalization Techniques (96)
Graph-Based Algorithms for Similarity Search (44)
Dynamic Graph Learning Methods (42)
Benchmarking Graph Neural Networks (25)
Graph Transformer Architectures (23)
Robust Graph Anomaly Detection (17)
Federated and Privacy-Preserving Learning 251
This topic investigates techniques for training models across decentralized datasets while maintaining user privacy and data protection.
federated learning (12)
Sub-topics:
Robustness to Adversarial Distribution Shifts (58)
Decentralized Learning Mechanisms (57)
Trustworthy Federated Learning (55)
Weight Averaging Techniques (35)
Adaptive Protocols for Privacy (25)
Private Quantile Estimation (16)
Meta-Learning Approaches 221
This topic covers the study of learning algorithms that improve their performance on tasks through the adaptation of learning strategies themselves.
optimization methodshyperparameter tuninglearning to learnadaptive algorithms
Sub-topics:
Task Generalization Techniques (81)
Dynamic Model Adaptation (69)
Performance Benchmarking in Meta-Learning (25)
Knowledge Distillation Approaches (19)
Multi-Task Learning Algorithms (16)
Federated Learning in Meta-Learning (9)
Image Generation and Customization 216
This field explores methods for generating and customizing images based on specific attributes or contextual information.
diffusion models (6)
Sub-topics:
Generative Model Improvements (124)
Evaluation Benchmarks for Generative Models (41)
Data Augmentation Strategies (18)
Multi-modal Image Generation (11)
Diffusion Model Applications (11)
Adaptive Convolution Techniques (6)
Defensive Strategies in AI 211
This field examines methods to enhance the robustness and safety of AI models against various forms of attacks and vulnerabilities.
adversarial attacks (2)
Sub-topics:
Robust Neural Network Architectures (132)
Model Calibration Under Uncertainty (33)
Evaluation Benchmarks for Robustness (19)
Privacy-Preserving Learning Techniques (14)
Adversarial Training Approaches (5)
Unlearning and Data Removal Techniques (5)

NAACL 2025

North American Chapter of ACL 1,957 papers
+
Causal Learning in NLP 497
Research focused on applying causal learning methods to address spurious correlations in natural language processing tasks.
causal inference (2)spurious correlations (1)text classification (4)
Sub-topics:
Causal Benchmarks for Language Understanding (137)
Causal Impact Analysis of Language Generation (85)
Causal Mechanisms in Dialogue Systems (80)
Causal Interpretability of Language Models (71)
Identifying Causal Features in Text (59)
Causal Inference in Language Models (38)
Data Augmentation Techniques 347
Techniques for enhancing training datasets, particularly focusing on few-shot scenarios and relation extraction tasks.
relation extraction (4)
Sub-topics:
Dynamic Data Augmentation (108)
Contextual Data Enrichment (80)
Multi-Modal Augmentation (64)
Label-Free Data Filtering (36)
Noise-Enhanced Training (30)
Sampling Strategies for Imbalanced Datasets (25)
Multimodal Learning Systems 221
Exploring the integration of multiple modalities, such as text and audio, to improve performance in specific tasks like clinical forecasting.
multimodal transformersclinical forecastinghybrid approachesaudio-visual integration
Sub-topics:
Contextualized Multimodal Understanding (52)
Cross-Modal Learning Techniques (47)
Bias and Fairness in Multimodal Models (45)
Multimodal Evaluation Benchmarks (41)
Adaptive Multimodal Representation (23)
Visual Question Answering Frameworks (7)
Unlimited Reasoning Capabilities 218
Enhancing reasoning capabilities of models through innovative techniques like reverse thinking and step-by-step reasoning frameworks.
chain-of-thoughtlogical reasoningmodels verificationreverse thinking
Sub-topics:
Dynamic Context Adaptation (47)
Robustness Evaluation Frameworks (42)
Multimodal Knowledge Integration (35)
Bias Detection and Mitigation (32)
Causal Reasoning Frameworks (22)
Interactive Dialogue Systems (19)
Hallucination Detection & Mitigation 142
Developing methods for detecting and mitigating hallucinations in generated outputs from large language models and other generative systems.
hallucination detection (2)information retrieval (1)
Sub-topics:
Dynamic Data Selection for Training (39)
Evaluation Metrics for Hallucinations (35)
Error Analysis in Multimodal Systems (30)
Contextual Relevance Assessment (21)
Bias Mitigation Techniques (17)
Conversational AI for Mental Health 135
Developing conversational agents aimed at unobtrusively diagnosing mental health conditions through dialogue.
dialogue systemssymptom probingmental health diagnosisnaturalistic conversations
Sub-topics:
Multi-modal Interaction Techniques (50)
User Privacy and Ethical Considerations (41)
Bias Mitigation in AI Systems (34)
Conversational Agents for Therapy (5)
Emotionally-Aware Dialogue Systems (3)
Prompt Engineering Strategies 117
Innovative methods for crafting prompts to optimally leverage large language models for specific tasks and domains.
in-context learning (3)fine-tuning (5)
Sub-topics:
Evaluating Prompt Effectiveness (38)
Prompt Optimization for Specific Tasks (38)
Multi-modal Prompting Techniques (18)
Dynamic Prompt Adjustment (13)
Bias Mitigation through Prompting (10)
Long-context Evaluation Metrics 91
Creating and assessing metrics tailored for evaluating models' performance in handling long-context inputs and generating coherent outputs.
long-context scenariosevaluation benchmarkstext generationattention visualization
Graph Representation Learning 84
Utilizing graph-based approaches for tasks such as entity disambiguation in verification processes and improving information access.
entity disambiguationinteractive graphsinformation retrievalknowledge graphs
Language Model Quantization Techniques 37
Investigating methods for quantizing large language models to enhance performance while reducing computational costs.
model efficiencymemory optimizationquantization techniquescomputation reduction

ACL 2024

Association for Computational Linguistics 2,873 papers
+
Causal Fact Verification 256
Research focusing on verifying causal claims through the analysis of argument structures.
argument structure (1)causal reasoning (2)verification (5)
Sub-topics:
Causal Inference in Language Models (68)
Causal Relationship Extraction (49)
Benchmarking Causal Reasoning (46)
Data Quality in Causal Verification (35)
Misinformation Detection Algorithms (32)
Contradiction Detection Methods (15)
Data Augmentation for NLP 206
Methods to augment textual datasets for improving performance in NLP tasks using synthetic data generation.
synthetic data (5)abusive language detection (1)
Sub-topics:
Evaluation Benchmarks for Augmented Data (56)
Domain Adaptation through Augmentation (47)
Contextual Information for Data Augmentation (26)
Synthetic Data Generation Approaches (25)
Bias and Fairness Analysis in Augmentation (21)
Multimodal Data Augmentation Strategies (19)
Causal & Emotional Attribution in Language 122
Investigating how large language models associate emotions with arbitrary words and how this aligns with human perceptions.
emotional associations (1)nonsense words (1)language models (35)
Sub-topics:
Causal Inference in Text (44)
Causal Language Modeling (44)
Sentiment Analysis Frameworks (11)
Emotion Recognition Techniques (10)
Multi-task Emotion Detection (7)
Cross-lingual Emotional Attribution (6)
Factuality and Summarization Analysis 88
Evaluating the factual accuracy of summaries generated from texts using various inference techniques.
factuality evaluation (2)summarization (7)natural language inference (1)claim extraction (1)
Few-Shot Semantic Change Detection 39
Approaches leveraging few-shot learning to detect changes in the semantics of language over time.
few-shot learning (1)semantic change (4)GPT-4 (1)
Cognitive Modeling in Dialogue Systems 34
Research aimed at harmonizing dialogue systems with cognitive modeling to maintain character consistency during interaction.
persona integritydomain adaptationdialogue generationcognitive architecture
Human-Like Evaluation in Translation 33
Developing methods for assessing translation quality in a manner that aligns with human judgment.
error analysistranslation evaluationprompting techniqueshuman-like

AFA 2024

American Finance Association Annual Meeting 82 papers
+
Behavioral Preferences in Decision Making 16
This topic examines how individuals value simplicity when making economic decisions under risk.
simplicity preferencedecision under riskexperimental economicschoice behavior
Credit Market Dynamics and Leverage 14
This topic studies the relationship between broker-dealer leverage dynamics and their effect on credit supply during market disruptions.
leverage shocks (1)funding constraints (1)credit supply (1)financial stability (1)
Information Economics in Financial Markets 12
This area analyzes the interaction between information flows in financial markets and their impact on trading behaviors and asset pricing.
anomaly detectionmarket signalsinformation disseminationrisk premium
Asset Pricing Models and Market Performance 10
This research investigates the effectiveness of various asset pricing models in predicting credit spreads and market behavior.
credit spreadsdefault riskinvestment-grade modelsglobal markets
Financial Technology and Consumer Behavior 9
This research focuses on how automated financial notifications influence consumer financial behavior and reduce costs.
automatic enrollment (1)overdraft alerts (1)field experiments (1)
Risk Management in Corporate Finance 9
This research evaluates the role of private equity in managing risks associated with corporate failures post-financial crisis.
private equityfailed-bank resolutionfinancial crisisrisk assessment
Behavioral Economics and Contract Theory 6
This research focuses on how psychological factors and strategic behavior impact contract design and incentive alignment in organizations.
principal-agent modelcontract manipulationeffort incentivesutility maximization
Consumer Debt and Labor Supply Responses 5
This topic examines how changes in mortgage payments influence household labor supply decisions and income adjustments.
mortgage payments (1)labor supply elasticity (1)
Environmental Economics and Market Behavior 3
This area analyzes the effects of environmental pressures on corporate behavior and market dynamics in the context of pollution.
greenwashing (1)asset market (1)pollution (1)sustainability (1)
Decentralized Finance Mechanisms 2
This area explores the functioning and implications of decentralized exchanges and automated liquidity mechanisms in finance.
Uniswap (1)automated market maker (1)liquidity provision (2)Ethereum blockchain (1)

CVPR 2024

Computer Vision and Pattern Recognition 2,716 papers
+
3D Reconstruction Techniques 240
Exploration of methods for reconstructing 3D shapes and scenes from 2D images or multi-view data.
3D reconstruction (4)keypoint detection (1)depth estimation (2)
Sub-topics:
General-Purpose 3D Neural Fields (157)
3D Point Cloud Upsampling (20)
Video-based 3D Object Detection (16)
3D Human Pose Estimation (14)
Geometric-Semantic Fusion (9)
3D Facial Expression Reconstruction (7)
Multimodal Learning Approaches 139
Methods that integrate and leverage multiple data modalities, such as images and text, for improved understanding and generation.
image captioning (1)cross-modal retrieval (1)
Sub-topics:
3D Object Detection (74)
Cross-Domain Few-Shot Segmentation (35)
Text-to-4D Scene Generation (18)
Emotion Representation and Expression Generation (5)
Audio-Visual Speech Recognition (5)
Diffusion Model Architectures 131
Research focused on the development and applications of diffusion models for tasks such as image generation and editing.
diffusion models (13)image generation (4)
Sub-topics:
3D Structural Reconstruction (51)
Conditional Denoising Techniques (32)
Real-time Diffusion Sampling (20)
Joint Motion Estimation (13)
Diffusion for Video Inpainting (8)
Score Distillation in Diffusion (7)
Image Restoration Techniques 115
Methods dedicated to recovering and enhancing image quality for various applications, including medical and document images.
image restoration (3)document image (1)
Sub-topics:
Image Denoising Algorithms (60)
Blind Image Super-Resolution (38)
Adaptive Deconvolution Techniques (8)
Generative Image Inpainting (5)
Spatial-Frequency Based Enhancement (4)
Task-Specific Prompt Engineering 78
Techniques aimed at optimizing prompts for specific machine learning tasks to enhance model performance.
prompt learning (2)text-to-image (5)few-shot learning (2)
Human Activity Recognition 70
Techniques for recognizing and understanding human behaviors and activities through video and sensor data.
human activity (1)action segmentation (1)
Creative Video Generation 67
Innovations in generating and editing videos creatively through AI-driven methods, including sound and imagery fusion.
video editing (2)
Federated Learning Strategies 42
Researching methods and frameworks for training machine learning models across distributed devices while ensuring data privacy.
federated learning (8)
Neural Radiance Fields Development 34
Advances in neural radiance fields for rendering and representing three-dimensional scenes through neural networks.
neural radiance fields (3)
Graph Neural Network Applications 20
Utilization of graph structures and neural computations for various tasks, such as ranking and learning from structured data.
graph neural networkssaliency rankingdomain separationsemantics

EACL 2024

European Chapter of ACL 791 papers
+
Sentiment Analysis in Regional Languages 188
Application of sentiment analysis techniques using sentence embeddings for Tamil and Tulu languages.
sentence embeddings (1)Dravidian languages (2)machine learning (5)
Sub-topics:
Sentiment Analysis Benchmarks (147)
Cross-Lingual Sentiment Transfer (14)
Aspect-Based Sentiment Analysis (12)
Sentiment Lexicon Development (5)
Emotion Detection in Regional Languages (5)
Multimodal Sentiment Analysis (5)
Fake News Detection 119
Utilization of a fine-tuned BERT model for detecting fake news in the Malayalam language.
multilingual modelsfine-tuned BERTsocial media analysisnatural language understanding
Sub-topics:
Multimodal Approaches to Verification (78)
Bias Analysis in News Content (23)
Stance Detection in Social Media (12)
Adversarial Training for Fake News (4)
Knowledge Graph Completion 91
Using large language models to enhance the completion of knowledge graphs through distillation processes.
contextualization distillation (1)language models (8)
Contrastive Decoding Techniques 76
Mitigation of hallucinations in machine translation through innovative contrastive decoding methods.
machine translation (5)hallucinations (1)
Social Reasoning in Language Models 65
Investigating the capabilities of large language models in understanding and reasoning about social behavior.
neural theory of mind (1)stress testing (1)large language models (8)
Personalized Summarization Tools 54
Creation of a lecture summarization tool tailored for humanities students using large language models.
LLMs (5)personalization (1)
Causal Mediation Analysis 47
Exploring causal mediation techniques to analyze and explain the dynamics of rumor detection in social contexts.
rumour detection (1)social media (1)
Accent Adaptation for ASR 46
Studying adaptations in automatic speech recognition systems to generalize across diverse African accents.
zero-shot learningautomatic speech recognitionaccent recognitiontransfer learning

EMNLP 2024

Empirical Methods in Natural Language Processing 3,104 papers
+
User-Centric Language Model Applications 387
Creating and evaluating language model-driven tools aimed at improving usability for specific user groups, especially in education.
usabilitydigital pedagogypersonalizationuser experience
Sub-topics:
Evaluating User-Centric Tasks (99)
Knowledge Enhancement Frameworks (79)
User Instruction Understanding (50)
Cultural and Linguistic Adaptation (47)
Bias Mitigation Techniques (43)
Interactive Language Generation (27)
Causal Reasoning in NLP 171
Focusing on the implementation of causal reasoning techniques in natural language processing tasks for more accurate predictions.
intent detection (1)
Sub-topics:
Applications of Causal Reasoning (118)
Evaluation Metrics for Causal Models (19)
Causal Inference Frameworks (18)
Causality Detection Techniques (13)
Memory Mechanisms in Language Models 76
Investigating the nature of memorization in large language models and its implications for performance and data efficiency.
verbatim memorizationoverfittinggeneralizationmodel interpretability
Cross-Lingual Language Understanding 74
Focusing on enhancing understanding and translation capabilities across multiple languages through advanced language models.
cross-lingual (6)language modeling (1)
Long-Context Language Models 68
Research focused on optimizing and evaluating large language models for effective question answering over extended contexts.
question answering (3)training (3)evaluation (2)
Emotion Recognition in Text 59
Exploring techniques to recognize and predict emotional content in text, enhancing user interaction in conversational systems.
emotion predictionconversational contextuser-generated contentmultitask learning
Adversarial Attacks on Language Models 46
Examining methods for conducting adversarial attacks against language models and assessing their robustness under various conditions.
robustness (2)distribution-aware (1)
Retrieval-Augmented Question Answering 39
Investigating retrieval-augmented methodologies to elevate the performance of question answering systems, specifically in complex queries.
retrieval systemsmulti-hop reasoningefficient inferenceQ&A systems
Language Model Distillation 35
Researching methods to streamline the capabilities of language models through distillation techniques to improve their efficiency and performance.
knowledge distillation (2)
Multimodal Historical Analysis 13
Developing models that combine visual and textual information to enhance analysis and understanding of historical events.
multi-modal (1)dynamic emulation (1)historical battles (1)

ICAIF 2024

ACM International Conference on AI in Finance 99 papers
+
Fraud Detection Techniques 15
Research focused on developing and evaluating methods to detect fraudulent activities in financial transactions.
transaction fraud (1)fraud models (1)bias audits (1)fairness metrics (1)
Financial Time Series Forecasting 14
Developing algorithms and models to predict financial metrics and trends based on historical time series data.
temporal graphsconditional GANsexplainable modelsstock predictions
Large Language Models in Finance 12
Utilizing large language models for analysis and comprehension of financial data, improving decision-making processes.
neural bandits (1)
Reinforcement Learning in Finance 11
Exploring the application of reinforcement learning methodologies to model and optimize financial strategies.
agent-based modelingmortgage simulatorrisk-based controlportfolio optimization
Adaptive Learning Strategies 8
Studying adaptive algorithms that learn and optimize strategies based on evolving data within financial contexts.
neural architecturelearning approachesdynamic adaptationssequential predictions
Unsupervised Learning in Finance 8
Investigating unsupervised techniques to reveal insights and structure within financial data without predefined labels.
clustering algorithmsalpha extractionfinancial patternsoutlier detection
Automated Market Making 7
Research on techniques to optimize market making processes and enhance liquidity in financial systems.
beta policies (1)linear programming (1)financial options (1)liquidity (1)
Quantitative Risk Management 6
Applying quantitative techniques to assess and manage risk in trading and investment scenarios.
quadratic variation (1)
Graph Neural Networks in Finance 6
Employing graph neural network architectures to analyze relationships in financial datasets for various applications.
dynamic graphsportfolio constructionfraud detectionasset pricing

ICML 2024

International Conference on Machine Learning 2,610 papers
+
Reinforcement Learning & Transfer Learning 405
This topic covers the integration of reinforcement learning techniques with transfer learning principles to improve adaptability.
policy optimization (5)dynamics shifts (1)continual learning (8)
Sub-topics:
Sample Efficiency in RL (270)
Exploration Strategies in RL (36)
Reward Shaping Techniques (25)
Transfer Learning in Deep RL (21)
Multi-Agent Reinforcement Learning (18)
Policy Gradient Algorithms (14)
Statistical Model Discovery Using Language Models 332
This research focuses on leveraging language models for automatic discovery and interpretation of statistical models.
language models (40)
Sub-topics:
Dynamic Representation Learning (102)
Robustness to Distribution Shifts (50)
Efficient Fine-tuning Techniques (43)
Integration of Graph Structures (39)
Bias Detection in Models (34)
Uncertainty Estimation Methods (30)
Self-Supervised Learning Paradigms 319
This research explores self-supervised learning methodologies to enhance feature extraction across different domains.
contrastive learning (5)
Sub-topics:
Unsupervised Learning Frameworks (105)
Robustness in Self-Supervised Models (74)
Feature Representation Learning (52)
Graph Neural Network Paradigms (31)
Next-Token Prediction Challenges (24)
Causal Inference in Self-Supervised Learning (19)
Causal Inference in Image Quality 279
This research focuses on utilizing causal inference techniques to enhance image quality assessment metrics.
Causal-IQA (1)image quality assessment (2)causal inference (5)generalization (7)
Sub-topics:
Causal Inference Algorithms (203)
Causal Models for Image Processing (24)
Bias and Fairness in Image Quality (18)
Interpretable Causal Inference in Imaging (12)
Image Quality Assessment Metrics (10)
Data Augmentation Techniques for Causality (8)
Graph Neural Networks for Structured Data 278
This work develops graph neural network techniques tailored for aggregate representations of molecular structures.
E(3)-invariancemolecular conformersaggregation networksgraph-based learning
Sub-topics:
Graph-based Representation Learning (71)
Graph Neural Network Architectures (65)
Robustness in Graph Learning (45)
Graph Neural Networks for Reinforcement Learning (36)
Graph-based Active Learning (30)
Interpretability of Graph Neural Networks (15)
Fairness and Bias in Machine Learning 239
This research investigates methods for identifying and mitigating biases in machine learning systems to promote fairness.
intersectional unfairness (1)
Sub-topics:
Evaluation of Model Bias (98)
Standardized Fairness Measures (56)
Non-Markovian Fairness Approaches (30)
Fairness in Sequential Decision Making (18)
Adversarial Attacks on Fairness (11)
Disparities in Feature Importance (10)
Adaptive Strategies in Simulation Environments 203
This topic focuses on developing adaptive learning strategies for optimizing policy performance in complex simulation settings.
policy optimization (1)reinforcement learning (2)
Sub-topics:
Dynamic Resource Allocation Techniques (68)
Robustness Benchmarking Frameworks (33)
Adaptive Learning Rate Strategies (27)
Causal Discovery in Simulated Environments (20)
Behavioral Diversity in Reinforcement Learning (18)
Simulation Robustness Analysis (13)
Diffusion Model Architectures 195
This area explores the theoretical and practical advancements in the architectures and applications of diffusion models.
Gaussian processes (1)inverse problems (3)
Sub-topics:
Applications of Diffusion Models (149)
Neural Diffusion Models (26)
Uncertainty Estimation in Diffusion (14)
Iterated Denoising Strategies (3)
Comparative Benchmarking of Diffusion Techniques (3)
Unsupervised Time Series Anomaly Detection 189
This topic explores advancements and challenges in unsupervised methods for detecting anomalies in time series data.
anomaly detection (3)time series (11)robustness (2)algorithms (1)
Sub-topics:
Representation Learning for Time Series (72)
Anomaly Detection Algorithms (42)
Dimensionality Reduction Techniques (29)
Evaluation Metrics for Anomaly Detection (25)
Multi-Modal Time Series Analysis (20)
Weakly Supervised Drug Response Prediction 98
This area investigates using weakly supervised learning models to improve predictions of drug response in cancer treatment.
representation learning (1)

NAACL 2024

North American Chapter of ACL 1,582 papers
+
Instruction Tuning & Alignment 363
Research focusing on the tuning and alignment of language models for specific tasks or multilingual contexts.
fine-tuning (8)prompt engineering (1)multilingual instruction (1)
Sub-topics:
Robustness in Instruction Tuning (96)
Evaluation Benchmarks for Instruction Tuning (68)
Data Augmentation for Instruction Tuning (51)
Cross-Lingual Alignment Techniques (49)
Dialogue and Conversational Adaptation (41)
Instruction-Tuned Multimodal Models (21)
Generative Forecasting Models 270
Investigating generative models for forecasting tasks based on temporal data represented in knowledge graphs.
forecasting (1)large language models (35)
Sub-topics:
Task-Specific Generative Applications (67)
Generative Text Modeling (52)
Evaluation of Generative Outputs (40)
Data Augmentation for Generative Models (35)
Improving Robustness in Generation (27)
Bias in Generative Models (21)
Causal Inference in NLP 191
Investigating causal relationships in natural language processing tasks, particularly in human-interactive settings.
human-language collaborationcausal reasoningcausal modelsinference methods
Sub-topics:
Causal Models for Language Understanding (95)
Causal Impact of Training Data (41)
Causal Benchmarks for Model Evaluation (27)
Bias Mitigation in NLP Models (22)
Counterfactual Reasoning in NLP (6)
Bias Detection & Mitigation 178
Studying the biases present in AI models and methodologies for detecting and mitigating these biases.
fairness (6)de-biasing (1)
Sub-topics:
Evaluating Bias in LLM Outputs (106)
Fairness in Data Annotation (29)
Cultural Sensitivity in AI Models (19)
Adversarial Techniques for Bias Detection (12)
Counterfactual Data Augmentation (9)
Clinical NLP Applications 106
Research on employing NLP techniques in clinical settings, such as coding and summarizing medical records.
clinical codingabstractive summarizationmedical NLPautomated systems
Sub-topics:
Knowledge Distillation Techniques (41)
Robustness in Medical NLP (28)
Automated Evaluation Frameworks (17)
Conversational Agents for Health (10)
Multimodal Processing in Healthcare (10)
Multimodal Emotion Analysis 105
Analysis of emotions in conversations using multiple modalities, including text and audio signals.
emotion recognition (4)emotion cause analysis (2)
Sub-topics:
Multimodal Data Fusion Techniques (34)
Contextual Emotion Detection (25)
Emotion Classification Benchmarks (21)
Cultural and Linguistic Variations in Emotion (17)
Emotion Recognition in Dialogue (8)
Hierarchical Text Classification 83
Developing neural network architectures focused on classifying texts into a structured hierarchy of labels.
multilabel classificationRNNsneural networkshierarchical models
Fact-Checking & Trustworthiness 81
Creating methodologies to ensure factual consistency and trustworthiness in statements generated by AI models.
fact-checking modulesgrounded reasoningtrustworthy AIsemantic verification
Role of Semantic Representations 72
Exploring how semantic representations influence the performance of large language models in NLP tasks.
large language models (9)
Knowledge Graph Integration 53
Utilizing knowledge graphs to enhance question answering and reasoning capabilities in AI systems.
semantic pruning (1)question answering (4)knowledge graphs (2)

NeurIPS 2024

Neural Information Processing Systems 4,494 papers
+
Optimization Techniques for Learning 179
Methods and frameworks focused on optimizing machine learning algorithms, enhancing both convergence rates and learning efficacy.
Minimax Optimization (2)Bayesian Optimization (2)
Sub-topics:
Robustness in Learning Algorithms (48)
Continuous and Online Learning (46)
Gradient-Based Optimization Methods (39)
Hyperparameter Optimization Strategies (24)
Multi-Objective Optimization Frameworks (13)
Bayesian Optimization Techniques (9)
Image Generation & Synthesis 154
Techniques that concentrate on generating and synthesizing images and video from various inputs, including 3D models and video diffusion.
3D Model AnimationSparse View SynthesisOccluded Pose EstimationDeepfake Detection
Sub-topics:
Benchmarking Image Generation Models (90)
3D Scene Generation Techniques (20)
Diffusion Models for Image Synthesis (8)
Language-Guided Image Generation (6)
Image Super-Resolution Approaches (3)
Causal Inference Strategies 153
Techniques for identifying causal relationships and effects in complex data settings, especially involving latent structures and sequential decision processes.
Marginal Structural Models (1)Latent Variables (1)
Sub-topics:
Benchmarking Causal Methods (63)
Robustness in Causal Inference (39)
Causal Graph Learning (22)
Causal Sequence Modeling (20)
Interventional Fairness Strategies (8)
Neural Program Learning 89
Focus on techniques that leverage neural networks to learn and synthesize programs to improve data efficiency in machine learning tasks.
Data EfficiencyNeural ComputationProgram SynthesisLearning to Learn
Large Scale Benchmarking 71
Establishment of comprehensive benchmarks for evaluating model performance across a variety of human-centric tasks and datasets.
Human-Centric (1)Referring Expression (1)
Graph-Based Learning Techniques 67
Explores methodologies that utilize graph structures for various learning tasks, focusing on improving analytical capabilities in complex relational data.
Graph Neural NetworksProfessional AnalysisKnowledge GraphsGraph Embeddings
Uncertainty Quantification Approaches 63
Research aimed at quantifying and managing uncertainty in predictive models and ensuring robust decision-making in uncertain environments.
Deep Ensembles (1)Confidence Calibration (1)
Diffusion Model Architectures 60
Research focusing on the design and optimization of models that utilize diffusion processes for various tasks including generation and knowledge distillation.
Denoising (1)
Time Series Analysis Techniques 60
Methods specifically designed to analyze and predict outcomes in time-dependent data, addressing both stationary and non-stationary challenges.
Forecasting (6)Dynamic Normalization (1)Segmentation (1)
Federated Learning Methodologies 47
Innovative approaches to federated learning that enhance privacy and performance in settings with limited labeled data and diverse objectives.
Privacy-PreservingFew-Shot LearningDecoupled Task-AgnosticDistributed Training

ACL 2023

Association for Computational Linguistics 3,203 papers
+
Transformers for Sequential Tasks 282
Exploration of transformer models' ability to comprehend and execute sequential instructions in various domains.
sequence-to-sequence (1)transformer architecture (1)natural language processing (1)
Sub-topics:
Robustness Evaluation in NLP (56)
Sequence-to-Sequence Learning (49)
Zero-Shot Language Processing (40)
Multi-Modal Learning Approaches (31)
Knowledge Distillation Techniques (30)
Emotion Recognition in Dialogues (29)
Dialogue Systems Evaluation 145
Investigation of methodologies to evaluate dialogue systems, particularly through the development of novel metrics like dialogue density.
open-domain dialogues (1)
Sub-topics:
Error Analysis in Dialogue Systems (42)
Benchmarking Dialogue System Performance (42)
User-Centric Evaluation Approaches (34)
Evaluation Metrics for Dialogue Systems (20)
Long-form Dialogue Evaluation (7)
Few-Shot Learning Approaches 101
Explores few-shot learning techniques that utilize minimal labeled data, leveraging adversarial cues to improve learning outcomes.
adversarial knowledge (1)contrastive prompting (1)language learners (1)
Sub-topics:
Benchmarking Few-Shot Learning Techniques (33)
Few-Shot Transfer Learning Approaches (32)
Evaluation Metrics for Few-Shot Learning (14)
Zero-Shot and Few-Shot Learning (12)
Meta-Learning for Few-Shot Tasks (10)
Knowledge-Based Question Answering 92
Development of systems that answer questions based on a structured knowledge base while using computational approaches for reasoning.
knowledge base (2)question answering (12)program induction (1)space debris (1)
Spurious Correlations Mitigation 85
Techniques to identify and mitigate unintended correlations in machine learning models, particularly in text-based applications.
text classificationspurious correlationdata biasresilience strategies
Emotion Recognition in Texts 79
Methods for identifying emotions in mixed-language text messages, leveraging tuning techniques to improve classification accuracy.
code-mixed languagesoft prompt tuningtext emotion classificationlinguistic features
Cross-Lingual Knowledge Transfer 67
Research methods aimed at transferring knowledge across different languages using multilingual models, particularly in resource-limited contexts.
cross-lingual transfer (3)low-resource languages (2)knowledge distillation (2)
Multimodal Summarization Techniques 60
Research on methods that integrate and summarize information from multiple modalities, such as text and images or audio.
coarse-to-fine approachmultimodal datacontent summarizationvisual-audio inputs
Explainable AI in Sentiment Analysis 29
Focuses on developing sentiment analysis models that provide understandable explanations for their predictions to enhance user trust.
explainable modelssentiment interpretationautomotive industryuser trust
Adversarial Training for NLP 28
Research focused on improving natural language processing models by training them against adversarial examples to enhance stability.
robustness (1)

AFA 2023

American Finance Association Annual Meeting 84 papers
+
Financial Market Communication 24
Analysis of how communication strategies in financial markets can lead to information black holes and affect project financing.
information asymmetryfinancial disclosuresrisk communicationmarket reactions
Complex Models in Finance 21
This research studies the advantages of using complex models over simple models for predicting market returns.
return predictability (1)market returns (1)
Insider Trading Dynamics 8
An analysis of how legal risks influence the trading behavior of insiders, particularly after regulatory shocks.
legal risk (1)insider trading (1)
Behavioral Biases in Trading 8
Research into how cognitive biases and heuristics influence the trading decisions and performance of institutional investors.
heuristicsinstitutional investorsbuying behaviorselling performance
Impact of News Positioning 6
An examination of how the positioning of financial news affects market reactions and price movements.
excess returns (1)
Entrepreneurial Financing Trends 6
Study of the effectiveness of angel investor tax credits in fostering entrepreneurial growth across states.
angel investor tax creditsentrepreneurshipstate-level analysisventure capital
Yield Curve Control Analysis 4
This topic focuses on the impact and effectiveness of yield curve control measures in addressing economic challenges, using case studies like Australia.
quantitative easing (1)yield curve control (1)
Option Trading Strategies 3
Investigation into the performance of options investments based on historical return patterns across different equities.
trading performance (1)
Shareholder Voting Mechanisms 2
Exploration of how trading activities shape shareholder voting outcomes and the implications for market governance.
shareholder democracyvoting behaviortrading effectsmarket structure
AI Talent Migration Impact 1
Research on how the migration of AI talent from universities affects entrepreneurial activity and startup funding in affected regions.
brain drain (1)entrepreneurship (1)

CVPR 2023

Computer Vision and Pattern Recognition 2,353 papers
+
Robustness and Generalization 187
Research aimed at enhancing the performance and reliability of models in the presence of adversarial conditions.
architectural design (1)cross-modal retrieval (1)domain adaptation (3)robust generalization (2)
Sub-topics:
Generalization in Few-Shot Learning (58)
Domain Adaptation Strategies (52)
Adversarial Robustness Techniques (38)
Robustness in Semantic Segmentation (27)
Test-Time Adaptation Approaches (12)
Point Cloud Processing 165
Techniques aimed at improving and manipulating point cloud data for various applications.
point cloud (13)
Sub-topics:
Point Cloud Analysis (135)
Point Cloud Segmentation (12)
3D Shape Reconstruction (10)
Geometric Feature Extraction (4)
Image Segmentation Techniques 149
Methods focusing on accurately delineating regions or objects within images.
saliency prompt (1)
Sub-topics:
Unsupervised Domain Adaptation for Segmentation (51)
3D Shape Reconstruction Techniques (46)
Active Learning for Segmentation (34)
Video Instance Segmentation (10)
Medical Image Segmentation (5)
Few-Shot Semantic Segmentation (3)
Knowledge Transfer in Machine Learning 134
Techniques that enable models to effectively transfer knowledge from one task or domain to another.
incremental learning (2)knowledge distillation (5)class attention transfer (1)domain adaptation (4)
Sub-topics:
Multi-Modal Knowledge Integration (58)
Domain Adaptation Techniques (37)
Knowledge Distillation Approaches (16)
Lifelong Learning Strategies (15)
Zero-Shot Learning Frameworks (8)
Multimodal Representation Learning 107
Approaches to learning interactions and representations that involve multiple data modalities like text and images.
vision-language (5)cross-modal (3)embedding (2)contrastive learning (3)
Sub-topics:
3D Shape Reconstruction (47)
Multimodal Action Recognition (29)
Human Pose Estimation (14)
Video Frame Interpolation (12)
Vision-Language Navigation (5)
Human Pose Estimation 58
Research focusing on techniques for estimating human poses from images or videos.
bottom-up (1)anchor-to-joint (1)
Generative Adversarial Networks (GANs) 51
Utilization of GAN architectures for generating and transforming images with high fidelity.
feature fusion (1)virtual re-staining (1)image synthesis (2)
Diffusion Models 47
Research on diffusion-based generative models that transform inputs into detailed outputs like images and videos.
video editing (1)3D-aware (1)
Temporal Action Localization 45
Methods that identify and classify actions in video sequences over time.
event perceptionweak supervisiontemporal groundingaction recognition
Face Recognition & Forgery Detection 28
Techniques for identifying and verifying human faces, as well as detecting manipulated images.
action units (1)forgery detection (1)

EACL 2023

European Chapter of ACL 729 papers
+
Document Processing & Summarization 140
Focusing on techniques for linking documents and generating summaries from complex textual sources.
question generation (2)
Sub-topics:
Event Extraction and Tracking (52)
Data Augmentation for Summarization (32)
Constructing Domain-Specific Summarization Benchmarks (20)
Evaluating Summary Quality (16)
Abstractive Summarization Techniques (13)
Multimodal Document Processing (7)
Low-Resource Language Processing 109
Developing techniques and frameworks for natural language processing and machine translation in low-resource languages.
indigenous languages (1)
Sub-topics:
Cross-Lingual Transfer Learning (31)
Evaluation Frameworks for Low-Resource NLP (23)
Data Augmentation Techniques (23)
Zero-Shot Learning Approaches (14)
Addressing Class Imbalance (9)
Multilingual Representation Learning (9)
Language Model Evaluation & Bias 98
Researching methods to evaluate and measure biases in language models using statistical and demographic data.
bias evaluation (2)descriptive bias (1)
Dialogue System Development 85
Creating advanced dialogue systems that track states and enhance interaction quality using various contextual techniques.
dialogue state tracking (3)persona-grounded dialogue (1)schema-guided dialogue (1)
Multi-Task Learning & Transfer Learning 66
Exploring models that leverage multitasking and transfer learning to enhance performance across various NLP tasks.
parameter-efficient tuning (1)domain adaptation (1)
Commonsense Knowledge Integration 57
Integrating commonsense knowledge into machine learning models to improve reasoning and contextual understanding.
knowledge graphs (1)
Entity Disambiguation & Identification 49
Developing models and methods to accurately identify and disambiguate entities within text and news articles.
entity definitions (1)entity recognition (2)
Text Augmentation Techniques 45
Investigating methods for augmenting text data to bolster training effectiveness and model robustness.
data augmentation (6)Levenshtein prediction (1)context-aware (1)
Phonological & Lexical Analysis 30
Conducting analyses that explore the phonological and lexical aspects of languages, focusing on historical and cross-lingual data.
phonological ontology (1)language history (1)
Skill Classification with Graphs 5
Utilizing graph neural networks to classify job skills from complex and diverse job descriptions.
extreme multi-label classification (1)graph neural networks (2)job skills (1)

EMNLP 2023

Empirical Methods in Natural Language Processing 2,932 papers
+
Language Model Evaluation 262
This topic addresses the methods and metrics for assessing the performance and fairness of language models.
quality metrics (1)reference-free metrics (1)
Sub-topics:
Evaluation Metrics for Language Models (114)
Contextual Understanding Assessment (46)
Bias Mitigation Techniques (31)
Evaluation of Multimodal Integration (27)
Human-Like Responses Evaluation (26)
Instruction Tuning Effects (11)
Data Augmentation Techniques 141
This research concentrates on enhancing training datasets to improve model robustness and performance through various augmentation strategies.
adversarial sample generation (1)data factors (1)noise learning (1)
Sub-topics:
Data Efficiency Strategies (83)
Domain Adaptation Methods (22)
Knowledge Distillation Approaches (17)
Active Learning Frameworks (15)
Prompt Tuning Techniques (4)
Text Generation Techniques 120
This area encompasses the development of methods and models specifically aimed at generating coherent and contextually relevant text.
data-to-text generation (1)text-to-SQL (2)
Sub-topics:
Evaluation Metrics for Generative Models (47)
Neural Network Architectures for Text Generation (44)
Multi-Modal Text Generation (16)
Controllable Text Generation (7)
Dialogue Generation in AI (6)
Zero-Shot Learning 98
This area investigates the capability of models to make predictions or perform tasks without prior specific training data for those tasks.
generalization (5)
Causal Reasoning & Analysis 85
This topic delves into understanding and modeling causal relationships in data, especially for applications in natural language processing.
event extraction (3)corporate performance changes (1)causal rationale (1)
Prompt Engineering 70
This topic focuses on techniques for crafting and optimizing prompts to improve the performance of language models in various tasks.
context-faithful prompting (1)
Language Model Robustness 69
Research focuses on ensuring language models can perform reliably under various conditions and resist adversarial perturbations.
factual associationsanalysing classical structuresblackbird language matricesattacks against models
Bias Mitigation in AI 58
This area investigates strategies to identify, measure, and reduce bias in AI systems, aiming for more equitable outcomes.
intersectional fairnessfairness definitionsdebiasing methodspreventing bias
Emotion Recognition & Generation 39
Research in this area focuses on understanding and generating emotional responses in dialogues to enhance human-computer interaction.
emotion annotations (1)dialogue quality (1)
Graph Neural Networks 18
This field explores the use of graph-based structures for improved reasoning and inference in various machine learning tasks.
graph-guided reasoningmedical-item graphevent causality inferencedepth of inference

ICAIF 2023

ACM International Conference on AI in Finance 79 papers
+
Generative Modeling in Finance 11
Research in this domain centers on the use of generative models to simulate financial data and develop risk management strategies.
GANs (1)
Reinforcement Learning in Finance 10
Research in this area explores the application of reinforcement learning techniques for optimizing financial decision-making and trading strategies.
deep hedging (2)
Natural Language Processing for Finance 10
This topic investigates the application of NLP techniques to analyze and extract insights from financial texts and reports for improved predictions.
financial analyst reports (1)LLMs (3)textual factors (1)
Financial Time-Series Forecasting 9
This topic focuses on methods and models for predicting financial time series data, addressing challenges such as volatility and structural dependencies.
volatility prediction (1)
Optimization Methods for Financial Models 8
Research focuses on optimization techniques to enhance the performance and reliability of financial models and simulations.
gradient-assisted calibration (1)
Statistical Arbitrage Techniques 8
This topic encompasses methods for identifying and exploiting pricing inefficiencies in financial markets through statistical methods.
portfolio optimization (1)financial networks (1)
Anomaly Detection in Finance 7
This topic encompasses methodologies for detecting anomalies in financial data and events to improve risk management and decision-making.
human-in-the-loop (1)
Graph Neural Networks for Finance 6
Research focuses on leveraging graph neural network architectures to model complex relationships and dynamics within financial networks and transactions.
dynamic graphs (1)
Event-Driven Market Analysis 3
This area focuses on understanding market reactions to significant events and their impact on financial metrics through advanced analytical techniques.
post-earnings driftevent series datacontextual factorseconomic links
Explainable AI in Finance 2
This area explores techniques for enhancing the interpretability and transparency of AI models applied to financial decision-making.
dual neural networks (1)

ICCV 2023

International Conference on Computer Vision 2,156 papers
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Object Detection & Tracking 253
Techniques and methodologies for detecting and tracking objects in images or videos, including both 2D and 3D contexts.
visual object tracking (2)3D object detection (9)
Sub-topics:
3D Object Detection Techniques (64)
Self-Supervised Learning for Object Detection (46)
Instance Segmentation Approaches (36)
Domain Adaptation for Object Detection (36)
Vision and Language Integration (23)
Benchmarking Object Detection Models (22)
Generative Models & View Synthesis 166
Focuses on the development of generative models that can create new image views based on existing data, particularly in 3D environments.
novel view synthesis (2)image generation (10)neural radiance fields (6)
Sub-topics:
3D Object Detection Techniques (45)
Adversarial Training in Generative Models (37)
View Synthesis Algorithms (31)
Diffusion for Image Synthesis (20)
Point Cloud Generation Techniques (19)
3D Human Pose Estimation (14)
3D Human Pose Estimation 87
Methods focused on accurately estimating human poses in three-dimensional space, often leveraging video data and accounting for occlusions.
3D human modelingocclusion handlingjoint estimationvideo analysis
Meta-Learning Techniques 86
Exploration of methods that enhance learning efficiency and adaptability through techniques that leverage previous learning experiences.
forward transferbackward transferadaptive ensembleslearning from few samples
Adversarial Learning & Robustness 71
Research dedicated to improving the robustness of models against adversarial attacks and enhancing their performance under various adversarial conditions.
transferability (2)
Quantization & Model Efficiency 68
Techniques aimed at reducing the complexity of models while maintaining performance, particularly through quantization and efficient architectures.
quantization-aware trainingenergy-based modelselastic quantizationmodel compression
Diffusion Model Architectures 66
Research focused on the design and improvement of diffusion models for various applications, including image synthesis and conditional generation tasks.
image generation (2)
Light and Video Enhancement Techniques 66
Focuses on improving visual quality and interpretability of images and videos under challenging lighting conditions.
low-light video enhancement (2)illumination disentanglement (1)semantic segmentation (3)
Graph and Spatial Reasoning 49
Research focused on representing and utilizing spatial relationships and graphical structures in understanding and processing data.
spatial knowledge distillation (1)
In-Context Learning & NLP 41
Techniques that leverage context to enhance learning and performance in NLP tasks, particularly through in-context demonstrations.
document information extraction (1)

ICML 2023

International Conference on Machine Learning 1,828 papers
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Efficient Algorithms for ML 389
This topic investigates techniques aimed at improving the efficiency and effectiveness of machine learning algorithms and model inference.
compute-lite (1)distillation (7)inference (5)
Sub-topics:
Dynamic Optimization Strategies (110)
Robust Learning Techniques (63)
Graph Neural Network Efficiency (48)
Privacy in Learning Algorithms (41)
Distributed Optimization Techniques (38)
Advanced Variational Inference Methods (37)
Probabilistic Inference and Learning 269
This topic revolves around methods for making probabilistic inferences and learning patterns within uncertain models.
variational inferencestructural biasesnonlinear Markov chainsself-normalization
Sub-topics:
Statistical Learning Theory (51)
Online Learning Strategies (50)
Generative Modeling Approaches (49)
Causal Inference Methods (34)
Uncertainty Quantification (25)
Exploration Techniques in Reinforcement Learning (23)
Reinforcement Learning Frameworks 202
This topic covers advancements in reinforcement learning techniques and frameworks designed to optimize decision-making in dynamic and complex environments.
policy gradient (6)actor-critic (3)multi-goal (1)exploration (9)
Sub-topics:
Exploration Strategies in RL (86)
Model-Based Reinforcement Learning (30)
Transfer Learning in RL (25)
Multi-Agent Reinforcement Learning (20)
Off-Policy Learning Algorithms (19)
Temporal Difference Learning (9)
Causal Inference in ML 177
Research in this area focuses on methodologies for understanding and estimating causal relationships within machine learning models.
causal effects (4)multi-task learning (2)belief representations (1)
Sub-topics:
Causal Representation Learning (120)
Causal Discovery Algorithms (32)
Counterfactual Inference Techniques (9)
Confounding Variable Adjustment (8)
Interventional Data Analysis (8)
Image and Speech Processing 169
This area addresses advancements in processing and generating visual and auditory information using machine learning techniques.
weak supervision (1)
Sub-topics:
Robustness in Image Classification (91)
Latent Variable Models for Images (29)
Text-to-Image Generation (7)
Generative Models for Speech (4)
Action Recognition in Videos (4)
Temporal Data Processing in Speech (3)
Graph Neural Networks 160
This research area explores novel approaches and enhancements in graph neural networks for processing and understanding graph-structured data.
multigrid (1)
Sub-topics:
Graph-based Learning Applications (49)
Robustness in Graph Neural Networks (39)
Learning Dynamics on Graphs (37)
Graph Neural Network Architectures (32)
Attention Mechanisms in GNNs (3)
Stochastic Dynamics and Games 106
Research in this category investigates the learning and optimization of strategies in stochastic environments and games.
mean-field (1)
Sub-topics:
Adaptive Algorithms for Stochastic Processes (42)
Causal Inference in Dynamic Systems (23)
Reinforcement Learning with Stochastic Dynamics (18)
Differentially Private Stochastic Optimization (14)
Online Learning in Stochastic Games (9)
Adversarial Robustness in Learning 96
Research here focuses on developing strategies to enhance the robustness of machine learning models against adversarial attacks.
adversarial training (2)
Diffusion Model Architectures 81
This topic involves the development and application of diffusion models for generating data across various modalities.
energy-based modelsmasked transformerscompositional generationreflected diffusion
Hyperparameter Optimization 59
Focused on techniques for tuning hyperparameters in machine learning models to improve performance and efficiency.
conformal quantile regressionadaptive explorationvariational inferencetest-time adaptation

NeurIPS 2023

Neural Information Processing Systems 3,540 papers
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Dynamic Model Training Techniques 330
Advancement of algorithmic strategies for optimizing the training processes of machine learning models under various constraints.
Gradient Descent (3)
Sub-topics:
Data-Efficient Learning Techniques (95)
Dynamic Contextual Adaptation (94)
Active Learning Strategies (47)
Asynchronous Model Training (30)
Adaptive Learning Rate Techniques (24)
Mitigating Catastrophic Forgetting (19)
Reinforcement Learning Innovations 123
Investigation of novel approaches to enhance decision-making processes in reinforcement learning environments.
Function Approximation (1)
Sub-topics:
Skill Discovery in RL (22)
Reinforcement Learning for Visual Tasks (22)
Hierarchical Reinforcement Learning (16)
Multi-Objective Reinforcement Learning (5)
Data-Centric AI Evaluation 114
Methods to improve and evaluate the quality and effectiveness of datasets used in machine learning models.
Imitation Learning (1)
Sub-topics:
Benchmarking for Model Evaluation (52)
Robustness in Data Shifts (34)
Causal Inference in Evaluation (9)
Data Valuation Techniques (7)
Transfer Learning in Evaluation (7)
Bias Mitigation in SGD (5)
Causal Inference Models 110
Applying causal discovery techniques to infer relationships and improve interpretability in machine learning models.
Active Causal Discovery (1)Causal Interpretation (1)Multi-Fidelity Experiments (1)Knowledge Graphs (1)
Sub-topics:
Causal Inference Algorithms (47)
Causal Discovery Techniques (36)
Causal Effect Estimation (24)
Self-Supervised Learning Strategies 86
Exploration of alternative approaches and challenges in self-supervised learning, focusing on model generalization and bias mitigation.
Weak Supervision (1)
Multimodal Learning Approaches 59
Techniques aimed at improving learning from multiple modalities for enhanced model performance in related tasks.
Cross Modal GeneralizationIntegrated PerceptionAudio-Visual LocalizationPoint Cloud Understanding
Graph Neural Networks for Dynamics 55
Application of graph neural networks to analyze and model dynamic, structured data in various domains.
Dynamical Systems (1)Link Prediction (1)
Adversarial Robustness Techniques 53
Research focusing on enhancing model performance and resilience against adversarial attacks and noisy inputs.
Certified RobustnessStable LearningNoise MitigationModel Perturbation
Transformer Architectures for NLP 26
Utilization and modification of transformer models for improved natural language understanding and generation tasks.
Directed Acyclic TransformersSelf-Attention MechanismContextual EmbeddingsPrompt Tuning
Federated Learning Frameworks 9
Research on techniques improving the efficiency and robustness of decentralized machine learning models while ensuring privacy.
Vertical Federated Learning (1)Communication Efficiency (1)

ICAIF 2022

ACM International Conference on AI in Finance 60 papers
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Reinforcement Learning for Finance 10
Research focused on applying reinforcement learning techniques to optimize trading strategies, pricing models, and risk management in financial markets.
dynamic pricingorder routingmodel calibrationportfolio management
Graph-Based Financial Modeling 10
Utilizing graph structures and neural networks to enhance predictions and understanding of financial systems and relationships.
graph neural networks (1)
Time Series Analysis in Finance 9
Focusing on methodologies for analyzing and forecasting financial time series data, accounting for stability and temporal dynamics.
asset ranking (1)
Fraud Detection Methodologies 8
Developing techniques and models aimed at detecting fraudulent activities in financial contexts, leveraging advanced learning paradigms.
self-supervised learning (1)
Optimization in Financial Algorithms 7
Methods for optimizing algorithmic performance in financial settings, including parameter tuning and robust design strategies.
mean-variance efficiency (1)
Synthetic Data Generation 6
Investigating techniques for generating synthetic data to bolster training and testing of financial models, emphasizing robustness and variety.
data augmentationstyle transferGANsself-supervision
Model Calibration Techniques 3
Developing and refining methods to accurately calibrate financial models based on observed data, enhancing predictive capabilities.
bayesian methodsoutput seriesparameter estimationdynamic models
Multi-Agent Systems in Finance 3
Exploring frameworks where multiple agents interact within financial systems, facilitating novel strategies and insights into market behavior.
collaborative learningagent-based modelingmean field controlorder flow dynamics
Credit Scoring Models 2
Investigating machine learning approaches for developing credit scoring models that meet regulatory requirements while ensuring accurate assessments.
monotonic neural networksstatistical learningrisk assessmentpredictive stability
Market Mechanism Design 2
Research on designing mechanisms and structures in financial markets to enhance efficiency and fairness among participants.
equitable marketplacecontract designincentivesmarket making

ICAIF 2021

ACM International Conference on AI in Finance 52 papers
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Market Simulation Techniques 8
This topic investigates various methods for accurately simulating financial markets, including techniques for discrete events and multiple interacting agents.
discrete event simulation (1)
Reinforcement Learning in Finance 8
This topic focuses on the application of reinforcement learning techniques to automate and optimize trading strategies and portfolio management in financial markets.
deep reinforcement learning (2)portfolio management (1)
Financial Risk Modeling 7
This topic focuses on leveraging machine learning techniques to improve the modeling and prediction of financial risks associated with various investment portfolios.
deep risk modelslatent risk factorscovariance matrix estimationrisk prediction
Imbalanced Data Handling 7
Research here emphasizes techniques to effectively manage and learn from imbalanced datasets, particularly within financial contexts like fraud detection and trading.
active learning (1)cold start (1)
Graph-Based Financial Analysis 5
Research in this arena utilizes graph-based learning techniques to analyze complex relationships and structures within financial datasets, such as funds or corporate mergers.
graph neural networksfund similaritymerger predictionnetwork modeling
Adversarial Robustness in Trading Algorithms 4
This topic centers on the challenges and solutions related to enhancing the robustness and security of machine learning algorithms used in trading against adversarial manipulation.
adversarial attacks (1)high-frequency trading (1)
Agent-Based Models in Finance 4
This area explores the use of agent-based models to analyze and simulate the behaviors and strategies of market participants in various financial scenarios.
equilibrium strategiesmarket maker analysisstrategic adoptiongame theory
Natural Language Processing for Finance 4
This topic focuses on employing natural language processing techniques to extract insights from financial texts and documents to predict market trends.
stock price prediction (1)
Generative Models for Market Data 2
Research in this area concentrates on using generative models, such as GANs, to realistically simulate financial market data for better analysis and strategy development.
GANstime series generationsimulated market dataconditional generation
Privacy-Preserving Finance Solutions 1
Research in this area focuses on developing methodologies to safeguard individual or institutional financial data while still performing analytics and operations.
privacy preservationsecure transactionsdata securityportfolio privacy

ICAIF 2020

ACM International Conference on AI in Finance 53 papers
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Deep Learning for Time Series Forecasting 13
Utilization of deep learning architectures specifically designed for forecasting and analyzing financial time series data.
conditional mutual information (1)financial time series (1)
Automated Trading Systems 12
Investigation of automated systems that leverage machine learning and reinforcement learning investments for stock trading under varying market conditions.
stock trading strategiesensemble methodsdeep reinforcement learningfinancial modeling
Portfolio & Risk Management Techniques 6
Focus on the development and assessment of advanced techniques and models for managing risk and optimizing portfolios in capital markets.
risk aversionhedging strategiessecurities lendingbayesian methods
Federated Learning for Financial Data 5
Exploration of federated learning techniques that enhance data privacy and collaboration in financial modeling without compromising sensitive information.
secure multi-party computation (1)financial applications (1)
Anomaly Detection in Transactions 5
Development of techniques to identify and mitigate anomalies in financial transaction data, leveraging machine learning methods.
subgraph anomaly detectionmoney laundering detectiontransaction networksunsupervised learning
Transaction Cost Optimization 4
Focus on optimizing trading strategies in relation to transaction costs, including the development of algorithms to minimize financial impact.
portfolio optimizationonline gradient descenttransaction costsscheduling strategies
Reinforcement Learning in Finance 3
Research focusing on the application of reinforcement learning techniques to modeling and optimizing financial decision-making processes.
batch reinforcement learning (1)
Market Sentiment Analysis 3
Research on extracting and analyzing sentiment from diverse data sources such as social media and news to understand market movements.
social media signalsconsumer perceptionsnews topic relevancestock market impact
Synthetic Data Generation in Finance 1
Investigation into methods for generating synthetic financial data to address the constraints of real-world data availability and its implications.
challenges (1)opportunities (1)
Image-Based Financial Analysis 1
Application of computer vision techniques to analyze and extract insights from financial documents and visual information.
image classificationfinancial documentsdeep learningvisual data extraction