Qitian Wu

Invariant Predict-and-Combinatorial Optimization under Distribution Shifts

Can Molecular Foundation Models Know What They Don't Know? A Simple Remedy with Preference Optimization

Physics-Inspired All-Pair Interaction Learning for 3D Dynamics Modeling

One Direction to Rule Them All: Toward Generalizable Solving Strategies Across Combinatorial Optimization Problems

DiffPuter: Empowering Diffusion Models for Missing Data Imputation

SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning

Regularizing Energy among Training Samples for Out-of-Distribution Generalization

Your Consistency Model is Secretly a More Powerful Supervised Learning Paradigm for Learning Tasks with Complex Labels

Supercharging Graph Transformers with Advective Diffusion

TabNAT: A Continuous-Discrete Joint Generative Framework for Tabular Data

Data-Centric Graph Condensation via Diffusion Trajectory Matching

Diffusion-Nested Auto-Regressive Synthesis of Heterogeneous Tabular Data

Toward Learning Generalized Cross-Problem Solving Strategies for Combinatorial Optimization

Inv-PnCO: Invariant Predict-and-Combinatorial Optimization under Distribution Shifts

Towards Generalization under Topological Shifts: A Diffusion PDE Perspective