10 papers
CoACT: Action-Preserving Observation Compression for Coding Agents
Haorui Chen, Yuancheng Zhu, Yitong Zhang +1
LLM-based coding agents solve software-engineering tasks through iterative interactions with development environments, where returned observations accumulate in the context and bec…
Grammar-Constrained Decoding Can Jailbreak LLMs into Generating Malicious Code
Yitong Zhang, Shiteng Lu, Jia Li
Large Language Models (LLMs) are increasingly used for code generation, raising concerns that they may be misused to produce malicious code. Meanwhile, Grammar-Constrained Decoding…
To See is Not to Master: Teaching LLMs to Use Private Libraries for Code Generation
Yitong Zhang, Chengze Li, Ruize Chen +4
Large Language Models (LLMs) have shown strong potential for code generation, yet they remain limited in private-library-oriented code generation, where the goal is to generate cod…
A Skill-augmented Agentic Framework and Benchmark for Multi-Video Understanding
Yue Zhang, Liqiang Jing, Jia Li +4
Multimodal Large Language Models have achieved strong performance in single-video understanding, yet their ability to reason across multiple videos remains limited. Existing approa…
CangjieBench: Benchmarking LLMs on a Low-Resource General-Purpose Programming Language
Junhang Cheng, Fang Liu, Jia Li +3
Large Language Models excel in high-resource programming languages but struggle with low-resource ones. Existing research related to low-resource programming languages primarily fo…
DiffuTester: Accelerating Unit Test Generation for Diffusion LLMs via Mining Structural Pattern
Lekang Yang, Yuetong Liu, Yitong Zhang +1
Diffusion large language models (dLLMs) enable parallel generation and are promising for unit test generation (UTG), where efficient and large-scale automated testing is essential…