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June 19, 2026 at 14:07 UTC
🤗 HuggingFace Daily Papers
Playful Agentic Robot Learning
▲ 29 🎓 University of California, Berkeley
  • Embodied robots learn reusable skills through self-directed play and exploration, then apply these skills to improve performance on downstream tasks w
S-Agent: Spatial Tool-Use Elicits Reasoning for Spatial Intelligence
▲ 23 🎓 NTU
  • S-Agent is a spatial reasoning framework that enhances visual language models with temporal memory and hierarchical spatial tools to enable continuous
Beyond Static Leaderboards: Predictive Validity for the Evaluation of LLM Agents
▲ 17 🏢 IBM
  • Aggregate-score leaderboards in agent benchmarks fail to capture deployment-relevant dimensions and show rank instability, necessitating new evaluatio
FreeStyle: Free Control of Style-Content Dual-Reference Generation from Community LoRA Min
▲ 15 🎓 Fudan University
  • FreeStyle is a scalable dual-reference generation framework that uses community LoRA mining to create large-scale style-content triplets while address
JanusMesh: Fast and Zero-Shot 3D Visual Illusion Generation via Cross-Space Denoising
▲ 12 🎓 National Yang Ming Chiao Tung University
  • A fast, training-free framework generates text-driven 3D visual illusions by decoupling generation into cross-space dual-branch denoising and view-con
FlowBender: Feedback-Aware Training for Self-Correcting Conditional Flows
▲ 10 🎓 Technion
  • FlowBender is a closed-loop framework that addresses constraint satisfaction in diffusion and flow models by training networks to correct alignment er
ENPIRE: Agentic Robot Policy Self-Improvement in the Real World
▲ 6 🏢 NVIDIA
  • ENPIRE framework enables autonomous robotics research through a closed-loop system that automates policy improvement via environment feedback, policy
Diffusion Backbone 1Local-Λ Mix Interaction 1Lλmi Block 1Spatial Contexts 1Global Semantic Priors 1Fixed-Size Linear Matrices 1Representation Bottleneck 1Adaptive Multi-Granularity Distillation 1Latent Space 1Gradient-Based Losses 1High-Fidelity Inpainting 1Parameter-Efficient Fine-Tuning 1
🏛️ Top Research Institutions
S-Agent: Spatial Tool-Use Elicits Reasoning for Spatial Intelligence
🏛️ NTU AI & Machine Learning
  • Existing vision-language models struggle with reasoning in dynamic 3D environments.
  • Introduction of S-Agent, a spatial tool-use framework that enhances reasoning capabilities for spatial intelligence.
JustDiag!: A Diagnostic Justification Engine for Accountable Root Cause Analysis
🏛️ Peking University Software & Programming
  • Large language models can produce fluent root cause analyses, but accountability in high-stakes operations requires more
  • JustDiag! is a diagnostic justification engine that provides evidence for accountability in root cause analysis.
A polynomial-time approximation scheme for minimum-weight decoding of topological codes
🏛️ Yale University Theory & Algorithms
  • Decoding of topological codes for fault-tolerant quantum computation is computationally challenging.
  • A polynomial-time approximation scheme for minimum-weight decoding of two-dimensional topological codes.
VEPHand: View-Efficient Photometric Hand Performance Capture at Scale
🏛️ Google Applications
  • Robust, high-fidelity 3D hand capture remains challenging due to geometric ambiguities in multi-view systems.
  • VEPHand introduces a view-efficient photometric hand performance capture method that balances rich photometry with geome
Who Wins the Conflict? Mechanistic Interpretability of Text Bias in Audio LLMs
🏛️ KAIST Other CS
  • Audio Large Language Models (Audio LLMs) exhibit a bias towards text over acoustic evidence, leading to hallucinations.
  • A mechanistic interpretability approach to analyze and mitigate text dominance in Audio LLMs.
Sharpe Ratio and Return-VaR Ratio Maximization for Option Portfolios with Skew-Elliptical
🏛️ McMaster University Quantitative Finance
  • Optimizing option portfolios under traditional assumptions may not capture the complexities of real-world return distrib
  • A formulation for optimal option portfolios that maximizes the Sharpe Ratio when underlying returns follow a skew-ellipt
Chaining Tasks, Redefining Work: A Theory of AI Automation
🏛️ MIT Economics
  • The integration of AI into production processes raises questions about how tasks are organized and executed.
  • A theory that categorizes production steps into manual, AI-augmented, and fully automated chains to optimize task bundli
AI & Machine Learning
471 papers 7 cats
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34 papers 6 cats
Software & Programming
35 papers 4 cats
Theory & Algorithms
26 papers 5 cats
Applications
120 papers 7 cats
Other CS
29 papers 8 cats
Quantitative Finance
10 papers 9 cats
Economics
10 papers 3 cats