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GAGPO: Generalized Advantage Grouped Policy Optimization2h◆UP-NRPA: User Portrait based Nested Rollout Policy Adaptation for Planning with Large Language Models in Goal-oriented Dialogue Systems2h◆Orchestra-o1: Omnimodal Agent Orchestration2h◆Hybrid Open-Ended Tri-Evolution Makes Better Deep Researcher2h◆WorkBench Revisited: Workplace Agents Two Years On2h◆Refusal Beyond a Single Direction: A Preliminary Comparison of Diff-in-Means and INLP2h◆YeasierAgent: Agentic Social Sandbox as a Canvas for Intent-Driven Creation of Platform-Agnostic Symbiotic Agent-Native Applications2h◆MA-ProofBench: A Two-Tiered Evaluation of LLMs for Theorem Proving in Mathematical Analysis2h◆A Multi-Agent AI System for Automated High School Transcript Processing: Collaborative Document Analysis at Scale2h◆Closing the Reflection Gap: A Free Calibration Bonus for Agentic RL2h◆SkillAudit: Ground-Truth-Free Skill Evolution via Paired Trajectory Auditing2h◆CSPO: Constraint-Sensitive Policy Optimization for Safe Reinforcement Learning2h◆Towards Direct Latent-Space Synthesis for Parallel Branches in LLM-Agent Workflows2h◆An Agentic Retrieval Framework for Autonomous Context-Aware Data Quality Assessment2h◆Aligning Quantum Operators with Large Language Models2h◆Safety-Contract Graph Multi-Agent Reinforcement Learning for Autonomous Network Security Response2h◆When Plausible Is Not Realistic: Evaluating Human Mobility in LLM-Based Urban Simulation2h◆Rethinking Backdoor Adversarial Unlearning through the Lens of Catastrophic Forgetting in Continual Learning2h◆Clay-CNN Hybrids: Leveraging Geo-Foundational Models as Auxiliary Context for Landslide Detection2h◆FEMOT: Multi-Object Tracking using Frame and Event Cameras2h◆GAGPO: Generalized Advantage Grouped Policy Optimization2h◆UP-NRPA: User Portrait based Nested Rollout Policy Adaptation for Planning with Large Language Models in Goal-oriented Dialogue Systems2h◆Orchestra-o1: Omnimodal Agent Orchestration2h◆Hybrid Open-Ended Tri-Evolution Makes Better Deep Researcher2h◆WorkBench Revisited: Workplace Agents Two Years On2h◆Refusal Beyond a Single Direction: A Preliminary Comparison of Diff-in-Means and INLP2h◆YeasierAgent: Agentic Social Sandbox as a Canvas for Intent-Driven Creation of Platform-Agnostic Symbiotic Agent-Native Applications2h◆MA-ProofBench: A Two-Tiered Evaluation of LLMs for Theorem Proving in Mathematical Analysis2h◆A Multi-Agent AI System for Automated High School Transcript Processing: Collaborative Document Analysis at Scale2h◆Closing the Reflection Gap: A Free Calibration Bonus for Agentic RL2h◆SkillAudit: Ground-Truth-Free Skill Evolution via Paired Trajectory Auditing2h◆CSPO: Constraint-Sensitive Policy Optimization for Safe Reinforcement Learning2h◆Towards Direct Latent-Space Synthesis for Parallel Branches in LLM-Agent Workflows2h◆An Agentic Retrieval Framework for Autonomous Context-Aware Data Quality Assessment2h◆Aligning Quantum Operators with Large Language Models2h◆Safety-Contract Graph Multi-Agent Reinforcement Learning for Autonomous Network Security Response2h◆When Plausible Is Not Realistic: Evaluating Human Mobility in LLM-Based Urban Simulation2h◆Rethinking Backdoor Adversarial Unlearning through the Lens of Catastrophic Forgetting in Continual Learning2h◆Clay-CNN Hybrids: Leveraging Geo-Foundational Models as Auxiliary Context for Landslide Detection2h◆FEMOT: Multi-Object Tracking using Frame and Event Cameras2h◆
News/GAGPO: Generalized Advantage Grouped Policy Optimization
arxiv
PublishedJune 15, 2026 at 4:00 AM
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GAGPO: Generalized Advantage Grouped Policy Optimization

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arXiv:2605.13217v1 Announce Type: cross Abstract: Reinforcement learning has become a powerful paradigm for post-training large language model agents, yet credit assignment in multi-turn environments remains a challenge. Agents often receive sparse, trajectory-level rewards only at the end of an epi

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