Author

Qiang Liu

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Preprint Aug 2026

HopRefusalBench: Diagnosing Refusal Failures in Search-Augmented Agents for Multi-Hop Reasoning

This work introduces HopRefusalBench, the first controlled benchmark of refusal within multi-hop search, and proposes a final-outcome taxonomy spanning target-aware refusal, pseudo-refusal, hallucinated completion, and search-budget exhaustion, together with source-aware trajectory metrics for post-trigger continuation...

Jianan Xie, Xin Sun, Zhongqi Chen et al. · 0 citations

Preprint Aug 2026

The Optimizer Is the Agent: Reasoning-Driven Search across Prompts, Programs, and ML Workflows

ReASearch is presented, a unified framework for reasoning-driven optimization in which the agent autonomously decides what to evaluate, how to diagnose failures, which edits to make, and when to verify or restart.

Jun-Bo Li, Bo-Yi Liu, Can-Wen Xu et al. · 1 citation

Preprint Jul 2026

RSPO: Reward-Swap Policy Optimization for Multi-Turn LLM Agents

Reinforcement learning holds significant potential for training large language models to handle multi-turn interactive tasks, but directly training with outcome rewards often results in slow convergence due to the sparsity of signals and the lack of fine-grained feedback.

Qiang Liu, Taian Guo, Ruizhi Qiao et al. · 0 citations