1 citations · 2 across the 10 of their papers we have counts for
4 papers · 1 filter
Lita: Light Agent Uncovers the Agentic Coding Capabilities of LLMs
Hankun Dai, Maoquan Wang, Mengnan Qi +6
Large language models (LLMs) are increasingly being applied to programming tasks, ranging from single-turn code completion to autonomous agents. Current code agent designs frequent…
SWE-bench Goes Live!
Linghao Zhang, Shilin He, Chaoyun Zhang +12
The issue-resolving task, where a model generates patches to fix real-world bugs, has emerged as a critical benchmark for evaluating the capabilities of large language models (LLMs…
Skeleton-Guided-Translation: A Benchmarking Framework for Code Repository Translation with Fine-Grained Quality Evaluation
Xing Zhang, Jiaheng Wen, Fangkai Yang +11
The advancement of large language models has intensified the need to modernize enterprise applications and migrate legacy systems to secure, versatile languages. However, existing…
DI-BENCH: Benchmarking Large Language Models on Dependency Inference with Testable Repositories at Scale
Linghao Zhang, Junhao Wang, Shilin He +13
Large Language Models have advanced automated software development, however, it remains a challenge to correctly infer dependencies, namely, identifying the internal components and…