activity
20232026
most citedStarCoder 2 and The Stack v2: The Next Generation

67 citations · 99 across the 13 of their papers we have counts for

collaborators
Showing cs.SEShow all

8 papers · 1 filter

cs.SE2026

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…

cs.SE2025

Toward Training Superintelligent Software Agents through Self-Play SWE-RL

Yuxiang Wei, Zhiqing Sun, Emily McMilin +6

While current software agents powered by large language models (LLMs) and agentic reinforcement learning (RL) can boost programmer productivity, their training data (e.g., GitHub i…

cs.SE2025

CWM: An Open-Weights LLM for Research on Code Generation with World Models

FAIR CodeGen team, Jade Copet, Quentin Carbonneaux +48

We release Code World Model (CWM), a 32-billion-parameter open-weights LLM, to advance research on code generation with world models. To improve code understanding beyond what can…

cs.SE2025

SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution

Yuxiang Wei, Olivier Duchenne, Jade Copet +6

The recent DeepSeek-R1 release has demonstrated the immense potential of reinforcement learning (RL) in enhancing the general reasoning capabilities of large language models (LLMs)…

cs.SE2024★ 2 cited

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…

cs.SE2024

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…

cs.SE2024

Productively Deploying Emerging Models on Emerging Platforms: A Top-Down Approach for Testing and Debugging

Siyuan Feng, Jiawei Liu, Ruihang Lai +4

While existing machine learning (ML) frameworks focus on established platforms, like running CUDA on server-grade GPUs, there have been growing demands to enable emerging AI applic…

cs.SE2024★ 67 cited

StarCoder 2 and The Stack v2: The Next Generation

Anton Lozhkov, Raymond Li, Loubna Ben Allal +63

The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder2. In partnership wi…