7 papers
InfiMed-ORBIT: Aligning LLMs on Open-Ended Complex Tasks via Rubric-Based Incremental Training
Pengkai Wang, Pengwei Liu, Qi Zuo +3
Reinforcement learning (RL) has powered many recent breakthroughs in large language models (LLMs), especially for tasks where rewards can be computed automatically, such as code ge…
TeachArena: Are Language Agents Ready for Realistic Teaching Work?
Zixin Chen, Peng Liu, Rui Sheng +6
Language agents are increasingly deployed in professional workflows, yet tutoring remains a high-stakes capability that existing evaluations only partially capture. Effective tutor…
Discovering Physical Directions in Weight Space: Composing Neural PDE Experts
Pengkai Wang, Pengwei Liu, Yuanyi Wang +7
Recent advances in neural operators have made partial differential equation (PDE) surrogate modeling increasingly scalable and transferable through large-scale pretraining and in-c…
PDEAgent-Bench: A Multi-Metric, Multi-Library Benchmark for PDE Solver Generation
Zhen Hang, Yushan Yashengjiang, Junhui Li +21
PDE-to-solver code generation aims to automatically synthesize executable numerical solvers from partial differential equation (PDE) specifications. This task requires not only und…
An Efficient Graph-Transformer Operator for Learning Physical Dynamics with Manifolds Embedding
Pengwei Liu, Xingyu Ren, Pengkai Wang +6
Accurate and efficient physical simulations are essential in science and engineering, yet traditional numerical solvers face significant challenges in computational cost when handl…
SAMora: Enhancing SAM through Hierarchical Self-Supervised Pre-Training for Medical Images
Shuhang Chen, Hangjie Yuan, Pengwei Liu +3
The Segment Anything Model (SAM) has demonstrated significant potential in medical image segmentation. Yet, its performance is limited when only a small amount of labeled data is a…