AHEAD: Adaptive Hindsight with Environment-Augmented Distillation for Agentic RL

arXiv:2608.24114 · cs.AI · Submitted 2026-08-25 · Read on arXiv

cs.AI

Submitted: 2026-08-25

Updated: 2026-08-25

Comments: 22 pages, 15 figures, 7 tables

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• GRPO — 106× in this paper · explained in 6 episodes
• Distillation — 52× in this paper · explained in 2 episodes
• Analyzer — 35× in this paper · explained in 1 episode
• Self-Distillation — 31× in this paper · explained in 7 episodes
• Reinforcement Learning — 16× in this paper · explained in 4 episodes
• Benchmark — 15× in this paper · explained in 2 episodes
• AUROC — 6× in this paper · explained in 2 episodes
• GRPO Objective — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Adaptive Hindsight with Environment-Augmented Distillation — 2× in this paper
• Credit assignment — 2× in this paper · explained in 3 episodes
• Meeting of the Association for Computational Linguistics — 2× in this paper
• Sample Efficiency — 2× in this paper · explained in 4 episodes
• World Model — 2× in this paper · explained in 7 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Action Space — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• In International Conference on Learning Representations — 1× in this paper
• On-Policy Distillation — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes

Sources

• On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
• Learning by Cheating
• Energy-Based Transfer for Reinforcement Learning
• Agentic Reinforced Policy Optimization
• Group-in-Group Policy Optimization for LLM Agent Training
• Self-Distillation Zero: Self-Revision Turns Binary Rewards into Dense Supervision
• Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps
• Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
• UI-S1: Advancing GUI Automation via Semi-online Reinforcement Learning
• UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning
• Self-Distilled Agentic Reinforcement Learning
• SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning
• ECHO: Terminal Agents Learn World Models for Free
• Skill-SD: Skill-Conditioned Self-Distillation for Multi-turn LLM Agents
• EnvRL: Learn from Environment Dynamics in Agentic Reinforcement Learning
• SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning
• Qwen2.5 Technical Report
• Qwen3 Technical Report

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