From the 1 of 39 linked papers with an AI index.
1 citations · 1 across the 8 of their papers we have counts for
29 papers · 1 filter
RepoReasoner: Evaluating Repository-Level Code Reasoning Ability of Long-Context Language Models
Yanlin Wang, Suiquan Wang, Yanli Wang +4
The paper presents RepoReasoner, a benchmark that evaluates how well large language models can reason about code across multiple files in a repository, testing both fine-grained ex…
WebDesignIter: Co-Evolving Design Knowledge for Repository-Level Front-End Code Generation
Zheng Pei, Mingwei Liu, Zhenxi Chen +2
Front-end development accumulates change after change at the repository level, weaving complex cross-file dependencies that current LLM coding agents tuned for single-shot tasks ca…
Dynamic analysis enhances issue resolution
Mingwei Liu, Zihao Wang, Zhenxi Chen +3
Resolving complex code defects from natural language descriptions remains a fundamental software engineering challenge. Recently, large language models (LLMs) have driven the creat…
Knowledge Matters: Injecting Project and Testing Knowledge into LLM-based Unit Test Generation
Anji Li, Mingwei Liu, Zhenxi Chen +5
Automated unit test generation using large language models (LLMs) holds great promise but often struggles with generating tests that are both correct and maintainable in real-world…
Knowledge-Graph-Driven Data Synthesis for Low-Resource Software Development: A HarmonyOS Case Study
Mingwei Liu, Zheng Pei, Yanlin Wang +5
In low-resource framework development (e.g., HarmonyOS), large language models (LLMs) often lack sufficient pre-training exposure, resulting in poor code generation performance. Al…
AdaDec: A Uncertainty-Guided Lookahead Decoding Framework for LLM-Based Code Generation
Kaifeng He, Mingwei Liu, Chong Wang +4
Code generation with large language models (LLMs) is highly sensitive to token selection during decoding, particularly at uncertain decision points that influence program logic. Wh…