5 papers
Off-Manifold Collapse in Guided Protein Language Models
Shuibai Zhang, Xinchi Liu, Fred Zhangzhi Peng +4
Protein language models are widely used priors for protein sequence design, and a growing body of work controls them at inference time as an alternative to fine-tuning. Such guidan…
ReJump: A Tree-Jump Representation for Analyzing and Improving LLM Reasoning
Yuchen Zeng, Shuibai Zhang, Wonjun Kang +9
Large Reasoning Models (LRMs) are Large Language Models (LLMs) explicitly trained to generate long-form Chain-of-Thoughts (CoTs), achieving impressive success on challenging tasks…
Free Draft-and-Verification: Toward Lossless Parallel Decoding for Diffusion Large Language Models
Shutong Wu, Jiawei Zhang
Diffusion Large Language Models (DLLMs) have emerged as a new paradigm of language modeling beyond autoregressive next-token prediction. Taking advantage of their inherent modeling…
VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data
Thomas Zeng, Shuibai Zhang, Shutong Wu +13
Process Reward Models (PRMs) have proven effective at enhancing mathematical reasoning for Large Language Models (LLMs) by leveraging increased inference-time computation. However,…
DiffusionPhase: Motion Diffusion in Frequency Domain
Weilin Wan, Yiming Huang, Shutong Wu +4
In this study, we introduce a learning-based method for generating high-quality human motion sequences from text descriptions (e.g., ``A person walks forward"). Existing techniques…