collaborators

9 papers

q-bio.BM2026

SurfDesign: Effective Protein Design on Molecular Surfaces

Fang Wu, Shuting Jin, Xiangru Tang +5

Protein function is largely determined by molecular surface geometry and physicochemical complementarity, yet most protein design methods condition only on backbone structure. We i…

cs.LG2026

Position: The Hidden Costs and Measurement Gaps of Reinforcement Learning with Verifiable Rewards

Fang Wu, Aaron Tu, Weihao Xuan +21

Reinforcement learning with verifiable rewards (RLVR) is a practical, scalable way to improve large language models on math, code, and other structured tasks. However, we argue tha…

cs.AI2026

Latent Action Reparameterization for Efficient Agent Inference

Wenhao Huang, Qingwen Zeng, Qiyue Chen +11

Large language model (LLM) agents often rely on long sequences of low-level textual actions, resulting in large effective decision horizons and high inference cost. While prior wor…

cs.CE2026

Pushing Biomolecular Utility-Diversity Frontiers with Supergroup Relative Policy Optimization

Xinwu Ye, He Cao, Hao Li +5

Biomolecular generators are often adapted with reward feedback to improve task-specific utility, but pushing utility alone can concentrate generation on a narrow family of candidat…

cs.LG2026

Hypergraph Pattern Machine: Compositional Tokenization for Higher-Order Interactions

Kyrie Zhao, Zehong Wang, Tianyi Ma +5

Hypergraphs model higher-order relations that drive real-world decisions, from drug prescriptions to recommendations. A central structural signal in such data, beyond what pairwise…

cs.LG2026

NoiseRater: Meta-Learned Noise Valuation for Diffusion Model Training

Fang Wu, Haokai Zhao, Da Xing +17

Diffusion models have achieved remarkable success across a wide range of generative tasks, yet their training paradigm largely treats injected noise as uniformly informative. In th…