Papers

• ContextBench: A Benchmark for Context Retrieval in Coding Agents (2026)
  Han Li et al.
  1.94
• Learning to Retrieve from Agent Trajectories (2026)
  Yuqi Zhou et al.
  1.94
• HiL-Bench (Human-in-Loop Benchmark): Do Agents Know When to Ask for Help? (2026)
  Mohamed Elfeki et al.
  1.94
• Latent Preference Modeling for Cross-Session Personalized Tool Calling (2026)
  Yejin Yoon et al.
  1.94
• Beyond Reasoning: Reinforcement Learning Unlocks Parametric Knowledge in LLMs (2026)
  Wanli Yang et al.
  1.94
• Precision Is Not Faithfulness: Coverage-Aware Evaluation of Grounded Generation with a Complete Oracle (2026)
  Juan S. Santillana
  1.94
• Beyond Monolingual Deep Research: Evaluating Agents and Retrievers with Cross-Lingual BrowseComp-Plus (2026)
  Yuheng Lu et al.
  1.94
• It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization (2025)
  Ali Behrouz et al.
  1.28
• Optimizing Retrieval-Augmented Generation: Analysis of Hyperparameter Impact on Performance and Efficiency (2025)
  Adel Ammar et al.
  1.28
• Provable Benefits of In-Tool Learning for Large Language Models (2025)
  Sam Houliston et al.
  1.28
• From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning (2025)
  Cheng Yang et al.
  1.28
• Olmo 3 (2025)
  Team Olmo et al.
  1.28
• L-CiteEval: Do Long-Context Models Truly Leverage Context for Responding? (2024)
  Zecheng Tang et al.
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• Eliminating Oversaturation and Artifacts of High Guidance Scales in Diffusion Models (2024)
  Seyedmorteza Sadat et al.
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