{"total":26,"rows":[{"id":"2509.02547","title":"The Landscape of Agentic Reinforcement Learning for LLMs: A Survey","created":"2025-09-02","cited_by_count":205,"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":"2510.08529","title":"CoMAS: Co-Evolving Multi-Agent Systems via Interaction Rewards","created":"2025-10-09","cited_by_count":29,"area":"agents"},{"id":"2603.02604","title":"Heterogeneous Agent Collaborative Reinforcement Learning","created":"2026-03-03","cited_by_count":15,"area":"agents"},{"id":"2505.17767","title":"Position: The Real Barrier to LLM Agent Usability is Agentic ROI","created":"2025-05-23","cited_by_count":12,"area":"agents"},{"id":"2603.06859","title":"Exact Is Easier: Credit Assignment for Cooperative LLM Agents","created":"2026-03-06","cited_by_count":9,"area":"agents"},{"id":"2506.02718","title":"End-to-End Optimization of LLM-Driven Multi-Agent Search Systems via Heterogeneous-Group-Based Reinforcement Learning","created":"2025-06-03","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":"2601.21742","title":"Epistemic Context Learning: Building Trust the Right Way in LLM-Based Multi-Agent Systems","created":"2026-01-29","cited_by_count":6,"area":"agents"},{"id":"2605.02801","title":"Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces","created":"2026-05-04","cited_by_count":5,"area":"agents"},{"id":"2505.21471","title":"Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration","created":"2025-05-27","cited_by_count":4,"area":"agents"},{"id":"2509.23870","title":"Gradient Coupling: The Hidden Barrier to Generalization in Agentic Reinforcement Learning","created":"2025-09-28","cited_by_count":3,"area":"agents"},{"id":"2509.24323","title":"MAS$^2$: Self-Generative, Self-Configuring, Self-Rectifying Multi-Agent Systems","created":"2025-09-29","cited_by_count":3,"area":"agents"},{"id":"2602.09578","title":"Rollout-Training Co-Design for Efficient LLM-Based Multi-Agent Reinforcement Learning","created":"2026-02-10","cited_by_count":2,"area":"agents"},{"id":"2608.09251","title":"MoRSE: Task-Oriented Multi-Agent System with Mixture of Role-Subtask Experts","created":"2026-08-10","cited_by_count":2,"area":"agents"},{"id":"2603.12631","title":"Joint Optimization of Multi-agent Memory System","created":"2026-03-13","cited_by_count":1,"area":"agents"},{"id":"2605.04811","title":"Tree-based Credit Assignment for Multi-Agent Memory System","created":"2026-05-06","cited_by_count":1,"area":"agents"},{"id":"2605.24202","title":"When Does Multi-Agent RL Improve LLM Workflows? Workflow, Scale, and Policy-Sharing Tradeoffs","created":"2026-05-22","cited_by_count":1,"area":"agents"},{"id":"2608.10299","title":"Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design","created":"2026-08-10","cited_by_count":1,"area":"agents"},{"id":"2509.21134","title":"ToMPO: Training LLM Strategic Decision Making from a Multi-Agent Perspective","created":"2025-09-25","cited_by_count":0,"area":"agents"},{"id":"2605.12943","title":"Reinforced Collaboration in Multi-Agent Flow Networks","created":"2026-05-13","cited_by_count":0,"area":"agents"},{"id":"2606.02812","title":"Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection","created":"2026-06-01","cited_by_count":0,"area":"agents"},{"id":"2608.11949","title":"ExRole: From Team Trajectories to Executable Roles in Multi-Agent Language Models","created":"2026-08-12","cited_by_count":0,"area":"agents"},{"id":"2609.04217","title":"At Equal Inference Cost, Multi-Agent Structure Does Not Beat a Single Frozen Agent","created":"2026-06-25","cited_by_count":0,"area":"agents"},{"id":"2609.29014","title":"AlphaDiverse: Post-Training Local Quantitative Research Agents for Diverse Exploration in Alpha Factor Mining","created":"2026-09-24","cited_by_count":0,"area":"agents"},{"id":"2609.32827","title":"Improving LLM Collaboration via Multi-Agent Preference Learning","created":"2026-09-26","cited_by_count":0,"area":"agents"}],"next_cursor":null}