4 citations · 12 across the 20 of their papers we have counts for
5 papers · 1 filter
AutoSpec: Safety Rule Evolution for LLM Agents via Inductive Logic Programming
Pingchuan Ma, Zhaoyu Wang, Zimo Ji +5
Large language model (LLM) agents increasingly automate complex tasks by integrating language models with external tools and environments. However, their autonomy poses significant…
Evaluating LLMs on Sequential API Call Through Automated Test Generation
Yuheng Huang, Jiayang Song, Da Song +4
By integrating tools from external APIs, Large Language Models (LLMs) have expanded their promising capabilities in a diverse spectrum of complex real-world tasks. However, testing…
Reasoning as a Resource: Optimizing Fast and Slow Thinking in Code Generation Models
Zongjie Li, Shuai Wang
This position paper proposes a fundamental shift in designing code generation models: treating reasoning depth as a controllable resource. Rather than being an incidental byproduct…
Refining Decompiled C Code with Large Language Models
Wai Kin Wong, Huaijin Wang, Zongjie Li +5
A C decompiler converts an executable into source code. The recovered C source code, once re-compiled, is expected to produce an executable with the same functionality as the origi…
Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach
Zhenlan Ji, Pingchuan Ma, Zongjie Li +1
While code generation has been widely used in various software development scenarios, the quality of the generated code is not guaranteed. This has been a particular concern in the…