activity
20242026
collaborators

20 papers

cs.AI2026

OSReward: Instituting Standardized Evaluation for Cross-Platform Computer-Use Reward Models

Qiushi Sun, Kanzhi Cheng, Yian Wang +20

The paper introduces OSReward, a benchmark for evaluating vision-language model judges that assess computer-using agent trajectories, and presents open reward models (OS‑Shepherd)…

cs.CL2026

OdysseyArena: Benchmarking Large Language Models For Long-Horizon, Active and Inductive Interactions

Hang Yan, Fangzhi Xu, Qiushi Sun +14

The rapid advancement of Large Language Models (LLMs) has catalyzed the development of autonomous agents capable of navigating complex environments. However, existing evaluations p…

cs.CL2026

LLMEval-Logic: A Solver-Verified Chinese Benchmark for Logical Reasoning of LLMs with Adversarial Hardening

Ming Zhang, Qiyuan Peng, Yinxi Wei +13

Evaluating large language models (LLMs) on natural-language logical reasoning is essential because rule-governed tasks require conclusions to follow strictly from stated premises.…

cs.CL2026

CL-bench Life: Can Language Models Learn from Real-Life Context?

Shihan Dou, Yujiong Shen, Chenhao Huang +35

Today's AI assistants such as OpenClaw are designed to handle context effectively, making context learning an increasingly important capability for models. As these systems move be…

cs.AI2026

ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflows

Qiushi Sun, Zhoumianze Liu, Chang Ma +18

Large Language Models (LLMs) have extended their impact beyond Natural Language Processing, substantially fostering the development of interdisciplinary research. Recently, various…

cs.LG2026

Balanced Aggregation: Understanding and Fixing Aggregation Bias in GRPO

Zhiyuan Zeng, Jiameng Huang, Zhangyue Yin +8

Reinforcement learning with verifiable rewards (RLVR) has become a central paradigm for improving reasoning and code generation in large language models, and GRPO-style training is…