7 papers
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
Yuchao Lin, Jacob Helwig, Shurui Gui +1
We consider achieving equivariance in machine learning systems via frame averaging. Current frame averaging methods involve a costly sum over large frames or rely on sampling-based…
Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning
Shubham Parashar, Shurui Gui, Xiner Li +8
We aim to improve the reasoning capabilities of language models via reinforcement learning (RL). Recent RL post-trained models like DeepSeek-R1 have demonstrated reasoning abilitie…
Object-Aware 4D Human Motion Generation
Shurui Gui, Deep Anil Patel, Xiner Li +1
Recent advances in video diffusion models have enabled the generation of high-quality videos. However, these videos still suffer from unrealistic deformations, semantic violations,…
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Xuan Zhang, Limei Wang, Jacob Helwig +60
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating…
Mitigating Spurious Correlations in LLMs via Causality-Aware Post-Training
Shurui Gui, Shuiwang Ji
While large language models (LLMs) have demonstrated remarkable capabilities in language modeling, recent studies reveal that they often fail on out-of-distribution (OOD) samples d…
Discovering Physics Laws of Dynamical Systems via Invariant Function Learning
Shurui Gui, Xiner Li, Shuiwang Ji
We consider learning underlying laws of dynamical systems governed by ordinary differential equations (ODE). A key challenge is how to discover intrinsic dynamics across multiple e…