2 citations · 4 across the 5 of their papers we have counts for
5 papers
SWE-Replay: Efficient Test-Time Scaling for Software Engineering Agents
Yifeng Ding, Lingming Zhang
Test-time scaling has been widely adopted to enhance the capabilities of Large Language Model (LLM) agents in software engineering (SWE) tasks. However, the standard approach of re…
SelfCodeAlign: Self-Alignment for Code Generation
Yuxiang Wei, Federico Cassano, Jiawei Liu +7
Instruction tuning is a supervised fine-tuning approach that significantly improves the ability of large language models (LLMs) to follow human instructions. We propose SelfCodeAli…
Evaluating Language Models for Efficient Code Generation
Jiawei Liu, Songrun Xie, Junhao Wang +3
We introduce Differential Performance Evaluation (DPE), a framework designed to reliably evaluate Large Language Models (LLMs) for efficient code generation. Traditional coding ben…
RepoQA: Evaluating Long Context Code Understanding
Jiawei Liu, Jia Le Tian, Vijay Daita +5
Recent advances have been improving the context windows of Large Language Models (LLMs). To quantify the real long-context capabilities of LLMs, evaluators such as the popular Need…
XFT: Unlocking the Power of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-Experts
Yifeng Ding, Jiawei Liu, Yuxiang Wei +2
We introduce XFT, a simple yet powerful training scheme, by simply merging upcycled Mixture-of-Experts (MoE) to unleash the performance limit of instruction-tuned code Large Langua…