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DSPO: Stable and Efficient Policy Optimization for Agentic Search and Reasoning

Chenyang Gu, Yewen Pu, Bruce Yang, Xiaofan Li, Huan Gao · Oct 10, 2025

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 98% Moderate protocol signal Freshness: Cold Status: Ready
Demonstrations Simulation Env General
  • Current approaches either rely on prompting to elicit the model's innate agent capabilities, or suffer from performance ceilings and collapse when applying RL to complex interactive tasks, leaving their true agentic potential untapped.
  • To address this, we introduce Dynamic-filter Sequence-level Policy Optimization (DSPO), an improved RL algorithm designed for robust agent training through sequence-level optimization and dynamic sample filtering.
Open paper
Structured Agent Distillation for Large Language Model

Jun Liu, Zhenglun Kong, Peiyan Dong, Changdi Yang, Tianqi Li, Hao Tang · May 20, 2025

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 98% Moderate protocol signal Freshness: Cold Status: Ready
Demonstrations Simulation Env General
  • Large language models (LLMs) exhibit strong capabilities as decision-making agents by interleaving reasoning and actions, as seen in ReAct-style frameworks.
  • We propose Structured Agent Distillation, a framework that compresses large LLM-based agents into smaller student models while preserving both reasoning fidelity and action consistency.
Open paper

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