From the 1 of 27 linked papers with an AI index.
10 papers · 1 filter
Confidence v.s. Critique: A Decomposition of Self-Correction Capability for LLMs
Zhe Yang, Yichang Zhang, Yudong Wang +3
Large Language Models (LLMs) can correct their self-generated responses, but a decline in accuracy after self-correction is also witnessed. To have a deeper understanding of self-c…
ExecRepoBench: Multi-level Executable Code Completion Evaluation
Jian Yang, Jiajun Zhang, Jiaxi Yang +9
Code completion has become an essential tool for daily software development. Existing evaluation benchmarks often employ static methods that do not fully capture the dynamic nature…
Evaluating and Aligning CodeLLMs on Human Preference
Jian Yang, Jiaxi Yang, Ke Jin +7
Code large language models (codeLLMs) have made significant strides in code generation. Most previous code-related benchmarks, which consist of various programming exercises along…
Qwen2.5-Coder Technical Report
Binyuan Hui, Jian Yang, Zeyu Cui +21
In this report, we introduce the Qwen2.5-Coder series, a significant upgrade from its predecessor, CodeQwen1.5. This series includes six models: Qwen2.5-Coder-(0.5B/1.5B/3B/7B/14B/…
Rotated Runtime Smooth: Training-Free Activation Smoother for accurate INT4 inference
Ke Yi, Zengke Liu, Jianwei Zhang +4
Large language models have demonstrated promising capabilities upon scaling up parameters. However, serving large language models incurs substantial computation and memory movement…
Aligning CodeLLMs with Direct Preference Optimization
Yibo Miao, Bofei Gao, Shanghaoran Quan +6
The last year has witnessed the rapid progress of large language models (LLMs) across diverse domains. Among them, CodeLLMs have garnered particular attention because they can not…