6 papers
The Verification Horizon: No Silver Bullet for Coding Agent Rewards
Binghai Wang, Chenlong Zhang, Dayiheng Liu +10
A classical intuition holds that verifying a solution is easier than producing one. For today's coding agents, this intuition is being inverted: as foundation models develop strong…
ZeroCoder: Can LLMs Improve Code Generation Without Ground-Truth Supervision?
Lishui Fan, Mouxiang Chen, Tingwei Zhu +4
Code generation is important in software engineering, and Reinforcement Learning with Verifiable Rewards (RLVR) is a powerful paradigm to improve it through execution-based feedbac…
Qwen3-Coder-Next Technical Report
Ruisheng Cao, Mouxiang Chen, Jiawei Chen +17
We present Qwen3-Coder-Next, an open-weight language model specialized for coding agents. Qwen3-Coder-Next is an 80-billion-parameter model that activates only 3 billion parameters…
SWE-Universe: Scale Real-World Verifiable Environments to Millions
Mouxiang Chen, Lei Zhang, Yunlong Feng +15
We propose SWE-Universe, a scalable and efficient framework for automatically constructing real-world software engineering (SWE) verifiable environments from GitHub pull requests (…
MegaFlow: Large-Scale Distributed Orchestration System for the Agentic Era
Lei Zhang, Mouxiang Chen, Ruisheng Cao +16
The rapid development of interactive and autonomous AI systems signals our entry into the agentic era. Training and evaluating agents on complex agentic tasks such as software engi…
SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner
Lei Zhang, Jiaxi Yang, Min Yang +6
We introduce **SWE-Flow**, a novel data synthesis framework grounded in Test-Driven Development (TDD). Unlike existing software engineering data that rely on human-submitted issues…