{"total":34,"rows":[{"id":"2404.14387","title":"A Survey on Self-Evolution of Large Language Models","created":"2024-04-22","cited_by_count":91,"area":null},{"id":"2502.11221","title":"PlanGenLLMs: A Modern Survey of LLM Planning Capabilities","created":"2025-02-16","cited_by_count":83,"area":null},{"id":"2603.04448","title":"SkillNet: Create, Evaluate, and Connect AI Skills","created":"2026-02-26","cited_by_count":53,"area":null},{"id":"2506.04625","title":"Advancing Tool-Augmented Large Language Models via Meta-Verification and Reflection Learning","created":"2025-06-05","cited_by_count":24,"area":null},{"id":"2503.04722","title":"Enough Coin Flips Can Make LLMs Act Bayesian","created":"2025-03-06","cited_by_count":22,"area":null},{"id":"2508.21456","title":"Morae: Proactively Pausing UI Agents for User Choices","created":"2025-08-29","cited_by_count":19,"area":null},{"id":"2604.24977","title":"A Survey on LLM-based Conversational User Simulation","created":"2026-04-27","cited_by_count":18,"area":null},{"id":"2410.23214","title":"Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval","created":"2024-10-30","cited_by_count":17,"area":null},{"id":"2603.08561","title":"RetroAgent: From Solving to Evolving via Retrospective Dual Intrinsic Feedback","created":"2026-03-09","cited_by_count":17,"area":null},{"id":"2605.10500","title":"SkillEvolver: Skill Learning as a Meta-Skill","created":"2026-05-11","cited_by_count":16,"area":null},{"id":"2509.25651","title":"AutoLabs: Cognitive Multi-Agent Systems with Self-Correction for Autonomous Chemical Experimentation","created":"2025-09-30","cited_by_count":15,"area":null},{"id":"2510.23564","title":"ReCode: Unify Plan and Action for Universal Granularity Control","created":"2025-10-27","cited_by_count":15,"area":null},{"id":"2505.16475","title":"ReflectEvo: Improving Meta Introspection of Small LLMs by Learning Self-Reflection","created":"2025-05-22","cited_by_count":12,"area":null},{"id":"2504.14128","title":"TALES: Text Adventure Learning Environment Suite","created":"2025-04-19","cited_by_count":11,"area":null},{"id":"2605.13625","title":"How to Interpret Agent Behavior","created":"2026-05-13","cited_by_count":10,"area":null},{"id":"2506.23127","title":"Unleashing Embodied Task Planning Ability in LLMs via Reinforcement Learning","created":"2025-06-29","cited_by_count":9,"area":null},{"id":"2505.13355","title":"Survey: Multi-Armed Bandits Meet Large Language Models","created":"2025-05-19","cited_by_count":7,"area":null},{"id":"2506.19794","title":"Why Do Open-Source LLMs Struggle with Data Analysis? A Systematic Empirical Study","created":"2025-06-24","cited_by_count":7,"area":null},{"id":"2510.00510","title":"JoyAgent-JDGenie: Technical Report on the GAIA","created":"2025-10-01","cited_by_count":7,"area":null},{"id":"2604.07774","title":"RoboAgent: Chaining Basic Capabilities for Embodied Task Planning","created":"2026-04-09","cited_by_count":7,"area":null},{"id":"2503.21383","title":"Controlling Large Language Model with Latent Actions","created":"2025-03-27","cited_by_count":5,"area":null},{"id":"2506.02827","title":"TO-GATE: Clarifying Questions and Summarizing Responses with Trajectory Optimization for Eliciting Human Preference","created":"2025-06-03","cited_by_count":5,"area":null},{"id":"2507.18858","title":"Weak-to-Strong Generalization with Failure Trajectories: A Tree-based Approach to Elicit Optimal Policy in Strong Models","created":"2025-07-25","cited_by_count":3,"area":null},{"id":"2603.13985","title":"Supervised Fine-Tuning versus Reinforcement Learning: A Study of Post-Training Methods for Large Language Models","created":"2026-03-14","cited_by_count":3,"area":null},{"id":"2602.02711","title":"Dynamic Mixed-Precision Routing for Efficient Multi-step LLM Interaction","created":"2026-02-02","cited_by_count":2,"area":null},{"id":"2603.29678","title":"View-oriented Conversation Compiler for Agent Trace Analysis","created":"2026-03-31","cited_by_count":2,"area":null},{"id":"2609.20056","title":"MAGMA-GEN: Validated Recovery Supervision from Ambiguous Failures via Counterfactual Re-Execution","created":"2026-09-17","cited_by_count":2,"area":null},{"id":"2510.01531","title":"Information Seeking for Robust Decision Making under Partial Observability","created":"2025-10-02","cited_by_count":1,"area":null},{"id":"2602.16833","title":"VAM: Verbalized Action Masking for Controllable Exploration in RL Post-Training -- A Chess Case Study","created":"2026-02-18","cited_by_count":1,"area":null},{"id":"2605.09192","title":"Evidence Over Plans: Online Trajectory Verification for Skill Distillation","created":"2026-05-09","cited_by_count":1,"area":null},{"id":"2412.00722","title":"Towards Adaptive Mechanism Activation in Language Agent","created":"2024-12-01","cited_by_count":0,"area":null},{"id":"2512.03762","title":"RoCo: Role-Based LLMs Collaboration for Automatic Heuristic Design","created":"2025-12-03","cited_by_count":0,"area":null},{"id":"2607.17621","title":"Mechanistic Attention Guidance for Agent Memory Refinement","created":"2026-07-20","cited_by_count":0,"area":null},{"id":"2609.25678","title":"Toolcompass: Guiding Tool Trialing, Not Suppressing It","created":"2026-09-22","cited_by_count":0,"area":null}],"next_cursor":null}