Author

Xiaomeng Hu

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Preprint Aug 2026

Getting the Parameters Right: A Difficulty-Graded Benchmark and Probe-Guided Training for LLM Tool Calls

Large language model agents derive much of their capability from tool use. Existing research on tool use has largely focused on selecting the right tool and orchestrating the order of calls. However, correctly filling the parameters of a tool call is equally critical for successful execution and has received far less a...

Guoyao Yu, Xiaoqing Sun, Ziqi Huang et al. · 0 citations

Jul 2026

Reasoning Error from Known Fact: Step-Level Self-Consistency Group Relative Policy Optimization for LLM

This work conducts a fine-grained analysis of hallucinations arising in LLM reasoning and finds that the reasoning traces are particularly prone to Context-Sensitive Factual Hallucinations: cases where the model actually has the relevant knowledge, yet makes factual errors due to contextual interference during reasonin...

Xiaomeng Hu, Jiaqi Hu, Hao Chen et al. · arXiv.org · 0 citations