collaborators

7 papers

cs.AI2026

WebGameBench: Requirement-to-Application Evaluation for Coding Agents via Browser-Native Games

Wenyu Zhang, Guoliang You, Tianlun +8

Coding agents are increasingly used as application builders, yet many evaluations still focus on source code, repository-level tests, or intermediate traces rather than the deliver…

cs.LG2026

Rollout Pass-Rate Control: Steering Binary-Reward RL Toward Its Most Informative Regime

Tianshu Zhu, Wenyu Zhang, Xiaoying Zuo +8

Agentic reinforcement learning (RL) for software engineering spends much of its compute on stateful trajectories whose grouped binary rewards are highly skewed and weakly contrasti…

cs.AI2026

AEM: Adaptive Entropy Modulation for Multi-Turn Agentic Reinforcement Learning

Haotian Zhao, Songlin Zhou, Yuxin Zhang +9

Reinforcement learning (RL) has substantially improved the ability of large language model (LLM) agents to interact with environments and solve multi-turn tasks. However, effective…

cs.AI2026

SWE-Hub: A Unified Production System for Scalable, Executable Software Engineering Tasks

Yucheng Zeng, Shupeng Li, Daxiang Dong +11

Progress in software-engineering agents is increasingly constrained by the scarcity of executable, scalable, and realistic data for training and evaluation. This scarcity stems fro…

cs.AI2026

LOGIGEN: Logic-Driven Generation of Verifiable Agentic Tasks

Yucheng Zeng, Weipeng Lu, Linyun Liu +9

The evolution of Large Language Models (LLMs) from static instruction-followers to autonomous agents necessitates operating within complex, stateful environments to achieve precise…

cs.LG2026

Kimi K2: Open Agentic Intelligence

Kimi Team, Yifan Bai, Yiping Bao +195

We introduce Kimi K2, a Mixture-of-Experts (MoE) large language model with 32 billion activated parameters and 1 trillion total parameters. We propose the MuonClip optimizer, which…