{"total":34,"rows":[{"id":"2504.20073","title":"RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning","created":"2025-04-24","cited_by_count":386,"area":"agents"},{"id":"2507.21046","title":"A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence","created":"2025-07-28","cited_by_count":170,"area":"agents"},{"id":"2503.24047","title":"Towards Scientific Intelligence: A Survey of LLM-based Scientific Agents","created":"2025-03-31","cited_by_count":98,"area":"agents"},{"id":"2509.08755","title":"AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning","created":"2025-09-10","cited_by_count":72,"area":"agents"},{"id":"2509.10446","title":"DeepDive: Advancing Deep Search Agents with Knowledge Graphs and Multi-Turn RL","created":"2025-09-12","cited_by_count":55,"area":"agents"},{"id":"2504.16078","title":"LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities","created":"2025-04-22","cited_by_count":41,"area":"agents"},{"id":"2607.14777","title":"SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning","created":"2026-07-16","cited_by_count":32,"area":"agents"},{"id":"2506.07972","title":"HeuriGym: An Agentic Benchmark for LLM-Crafted Heuristics in Combinatorial Optimization","created":"2025-06-09","cited_by_count":21,"area":"agents"},{"id":"2503.04094","title":"Pok\\'eChamp: an Expert-level Minimax Language Agent","created":"2025-03-06","cited_by_count":16,"area":"agents"},{"id":"2511.18538","title":"From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence","created":"2025-11-23","cited_by_count":15,"area":"agents"},{"id":"2509.10401","title":"Abduct, Act, Predict: Scaffolding Causal Inference for Automated Failure Attribution in Multi-Agent Systems","created":"2025-09-12","cited_by_count":14,"area":"agents"},{"id":"2505.18384","title":"Dynamic Risk Assessments for Offensive Cybersecurity Agents","created":"2025-05-23","cited_by_count":8,"area":"agents"},{"id":"2510.16720","title":"Beyond Pipelines: A Survey of the Paradigm Shift toward Model-Native Agentic AI","created":"2025-10-19","cited_by_count":8,"area":"agents"},{"id":"2602.19526","title":"How to Train Your Deep Research Agent? Prompt, Reward, and Policy Optimization in Search-R1","created":"2026-02-23","cited_by_count":8,"area":"agents"},{"id":"2603.11327","title":"Meta-Reinforcement Learning with Self-Reflection for Agentic Search","created":"2026-03-11","cited_by_count":8,"area":"agents"},{"id":"2606.14302","title":"Retrospective Progress-Aware Self-Refinement for LLM Agent Training","created":"2026-06-12","cited_by_count":6,"area":"agents"},{"id":"2412.13437","title":"Deploying Foundation Model Powered Agent Services: A Survey","created":"2024-12-18","cited_by_count":4,"area":"agents"},{"id":"2601.15141","title":"CLEANER: Self-Purified Trajectories Boost Agentic Reinforcement Learning","created":"2026-01-21","cited_by_count":4,"area":"agents"},{"id":"2601.22290","title":"The Six Sigma Agent: Achieving Enterprise-Grade Reliability in LLM Systems Through Consensus-Driven Decomposed Execution","created":"2026-01-29","cited_by_count":4,"area":"agents"},{"id":"2602.17547","title":"KLong: Training LLM Agent for Extremely Long-horizon Tasks","created":"2026-02-19","cited_by_count":4,"area":"agents"},{"id":"2603.12011","title":"Can RL Improve Generalization of LLM Agents? An Empirical Study","created":"2026-03-12","cited_by_count":4,"area":"agents"},{"id":"2605.30690","title":"ElasticMem: Latent Memory as a Learnable Resource for LLM Agents","created":"2026-05-29","cited_by_count":4,"area":"agents"},{"id":"2606.14211","title":"Closing the Reflection Gap: A Free Calibration Bonus for Agentic RL","created":"2026-06-12","cited_by_count":3,"area":"agents"},{"id":"2505.02709","title":"Technical Report: Evaluating Goal Drift in Language Model Agents","created":"2025-05-05","cited_by_count":2,"area":"agents"},{"id":"2605.16604","title":"R2V Agent: Teaching SLMs When to Ask for Help","created":"2026-05-15","cited_by_count":2,"area":"agents"},{"id":"2605.30712","title":"ExpGraph: Model-Agnostic Experience Learning with Graph-Structured Memory for LLM Agents","created":"2026-05-29","cited_by_count":2,"area":"agents"},{"id":"2605.19410","title":"Vision Harnessing Agent for Open Ad-hoc Segmentation","created":"2026-05-19","cited_by_count":1,"area":"agents"},{"id":"2606.04513","title":"MapAgent: An Industrial-Grade Agentic Framework for City-scale Lane-level Map Generation","created":"2026-06-03","cited_by_count":1,"area":"agents"},{"id":"2605.01567","title":"Feedback-Normalized Developer Memory for Reinforcement-Learning Coding Agents: A Safety-Gated MCP Architecture","created":"2026-05-02","cited_by_count":0,"area":"agents"},{"id":"2605.29625","title":"Improving Collaborative Storytelling with a Multi-Agent Framework Based on Large Language Models","created":"2026-05-28","cited_by_count":0,"area":"agents"},{"id":"2606.21740","title":"Training the Orchestrator: A Supervised Approach to End-to-End PDDL Planning with LLM Agents","created":"2026-06-19","cited_by_count":0,"area":"agents"},{"id":"2608.30322","title":"Ignorance or Incompetence? Constructing Knowledge-Gated, Verifiable Tasks for LLM Agents","created":"2026-08-31","cited_by_count":0,"area":"agents"},{"id":"2610.04087","title":"DUET: Co-Evolving Solver and Grader Agents","created":"2026-10-02","cited_by_count":0,"area":"agents"},{"id":"2610.19376","title":"DeLoop: Repeated Actions as Self-Supervision for Long-Horizon Agents","created":"2026-10-14","cited_by_count":0,"area":"agents"}],"next_cursor":null}