17 citations · 20 across the 8 of their papers we have counts for
9 papers
HarnessBridge: Learnable Bidirectional Controller for LLM Agent Harness
Xiaoxuan Wang, Haixin Wang, Alexander Taylor +3
Large language models are increasingly deployed as agents for long-horizon tasks, yet their performance is shaped not only by model capability and environment design, but also by t…
ARLArena: A Unified Framework for Stable Agentic Reinforcement Learning
Xiaoxuan Wang, Han Zhang, Haixin Wang +11
Agentic reinforcement learning (ARL) has rapidly gained attention as a promising paradigm for training agents to solve complex, multi-step interactive tasks. Despite encouraging ea…
MatSciBench: Benchmarking the Reasoning Ability of Large Language Models in Materials Science
Junkai Zhang, Jingru Gan, Xiaoxuan Wang +8
Large Language Models have shown strong scientific reasoning ability, but their performance on materials science problems remains less studied. To fill this gap, we introduce MatSc…
Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physics
Lianhao Zhou, Hongyi Ling, Cong Fu +14
Computing has long served as a cornerstone of scientific discovery. Recently, a paradigm shift has emerged with the rise of large language models (LLMs), introducing autonomous sys…
Entropy-Based Adaptive Weighting for Self-Training
Xiaoxuan Wang, Yihe Deng, Mingyu Derek Ma +1
The mathematical problem-solving capabilities of large language models have become a focal point of research, with growing interests in leveraging self-generated reasoning paths as…
Memorize and Rank: Elevating Large Language Models for Clinical Diagnosis Prediction
Mingyu Derek Ma, Xiaoxuan Wang, Yijia Xiao +4
Clinical diagnosis prediction models, when provided with a patient's medical history, aim to detect potential diseases early, facilitating timely intervention and improving prognos…
CliBench: A Multifaceted and Multigranular Evaluation of Large Language Models for Clinical Decision Making
Mingyu Derek Ma, Chenchen Ye, Yu Yan +4
The integration of Artificial Intelligence (AI), especially Large Language Models (LLMs), into the clinical diagnosis process offers significant potential to improve the efficiency…
Learning under Label Proportions for Text Classification
Jatin Chauhan, Xiaoxuan Wang, Wei Wang
We present one of the preliminary NLP works under the challenging setup of Learning from Label Proportions (LLP), where the data is provided in an aggregate form called bags and on…
SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models
Xiaoxuan Wang, Ziniu Hu, Pan Lu +7
Most of the existing Large Language Model (LLM) benchmarks on scientific problem reasoning focus on problems grounded in high-school subjects and are confined to elementary algebra…