Binhua Li

CATS: A Pragmatic Chinese Answer-to-Sequence Dataset with Large Scale and High Quality

2023

Liang Li, Ruiying Geng, Chengyang Fang, Bing Li, Can Ma, Rongyu Cao, Binhua Li, Fei Huang, Yongbin Li. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2023.

ExploraCoder: Advancing code generation for multiple unseen APIs via planning and chained exploration

2024 · arXiv (Cornell University)

Large language models face intrinsic limitations in coding with APIs that are unseen in their training corpora. As libraries continuously evolve, it becomes impractical to exhaustively retrain LLMs with new API knowledge. This limitation hampers …

SWE-GPT: A Process-Centric Language Model for Automated Software Improvement

2025 · Proceedings of the ACM on software engineering.

Large language models (LLMs) have demonstrated remarkable performance in code generation, significantly enhancing the coding efficiency of developers. Recent advancements in LLM-based agents have led to significant progress in end-to-end automatic software engineering (ASE), particularly …

Thinking Longer, Not Larger: Enhancing Software Engineering Agents via Scaling Test-Time Compute

2025 · arXiv (Cornell University)

Recent advancements in software engineering agents have demonstrated promising capabilities in automating program improvements. However, their reliance on closed-source or resource-intensive models introduces significant deployment challenges in private environments, prompting a critical question: \textit{How can …