4 citations · 9 across the 13 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
cs.AI2026
Do Tool Calls Execute as Intended? Measuring and Repairing Intent-Execution Correspondence in LLM Agents
Boyang Yang, Zhenhao Li, Ziyao Yang +4
Agents built on large language models (LLMs) build and run software through tool calls. A call reaches its program through several hops, and any hop can change the call without not…
cs.SE2026
CodeHacker: Automated Test Case Generation for Detecting Vulnerabilities in Competitive Programming Solutions
Jingwei Shi, Xinxiang Yin, Jing Huang +2
The evaluation of Large Language Models (LLMs) for code generation relies heavily on the quality and robustness of test cases. However, existing benchmarks often lack coverage for…