7 citations · 10 across the 19 of their papers we have counts for
4 papers · 2 filters
Efficient Grammar-Constrained Decoding via Parser Stack Classification
Yongmin Li, Yihong Dong, Jia Li +1
LLMs are widely used to generate structured output like source code or JSON. Grammar-constrained decoding (GCD) can guarantee the syntactic validity of the generated output, by mas…
Learning from Execution: Self-Evolving Memory for Private-Library Code Generation
Mofei Li, Taozhi Chen, Guowei Yang +1
Large Language Models (LLMs) have achieved strong performance on general code generation, but their effectiveness drops sharply in enterprise settings where software development re…
RealBench: A Repo-Level Code Generation Benchmark Aligned with Real-World Software Development Practices
Jia Li, Hongyi Deng, Yiran Zhang +9
Writing code requires significant time and effort in software development. To automate this process, researchers have made substantial progress using Large Language Models (LLMs) f…
KOCO-BENCH: Can Large Language Models Leverage Domain Knowledge in Software Development?
Xue Jiang, Ge Li, Jiaru Qian +12
Large language models (LLMs) excel at general programming but struggle with domain-specific software development, necessitating domain specialization methods for LLMs to learn and…