IGSD: Environment-Verified Hindsight Self-Distillation for Search Agents

arXiv:2609.32694 · cs.AI, cs.CL · Submitted 2026-09-26 · Read on arXiv

cs.AI, cs.CL

Submitted: 2026-09-26

Updated: 2026-09-26

Code: https://github.com/PhilipGAQ/igsd_code

Terminology

• Distillation — 43× in this paper · explained in 2 episodes
• Verification — 34× in this paper · explained in 2 episodes
• Information Gain — 21× in this paper · explained in 2 episodes
• Accuracy — 15× in this paper · explained in 1 episode
• GRPO — 13× in this paper · explained in 6 episodes
• Benchmark — 12× in this paper · explained in 2 episodes
• Self-distillation — 12× in this paper · explained in 6 episodes
• Ablation — 11× in this paper · explained in 1 episode
• AUC — 7× in this paper · explained in 2 episodes
• Reinforcement Learning — 7× in this paper · explained in 4 episodes
• GRPO Objective — 6× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• RAG — 3× in this paper · explained in 3 episodes
• Actor — 2× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• Information-Gain-Gated Self-Distillation — 2× in this paper
• Ablation Studies — 1× in this paper · explained in 1 episode
• Agentic Search — 1× in this paper · explained in 1 episode
• Credit assignment — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Introspection — 1× in this paper · explained in 2 episodes
• Reward Hacking — 1× in this paper · explained in 8 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning
• Group-in-Group Policy Optimization for LLM Agent Training
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
• Search-o1: Agentic Search-Enhanced Large Reasoning Models
• IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning
• Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning
• Self-Distilled Agentic Reinforcement Learning
• SD-Search: On-Policy Hindsight Self-Distillation for Search-Augmented Reasoning
• Qwen2.5 Technical Report
• Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning
• Information Gain-based Policy Optimization: A Simple and Effective Approach for Multi-Turn Search Agents
• Skill-SD: Skill-Conditioned Self-Distillation for Multi-turn LLM Agents
• Text Embeddings by Weakly-Supervised Contrastive Pre-training
• SmartSearch: Process Reward-Guided Query Refinement for Search Agents
• SIGHT: Reinforcement Learning with Self-Evidence and Information-Gain Diverse Branching for Search Agent
• LOTAPO: Leave-One-Turn Attribution for Self-Generated Process Rewards in Multi-Turn Search Reasoning

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