Xingyu Lu

UniCA: Unified Covariate Adaptation for Time Series Foundation Model

MiniOpt: Reasoning to Model and Solve General Optimization Problems with Limited Resources

Diversity-Driven Offline Multi-Objective Optimization via Bi-Level Pareto Set Learning

Kairos: Towards Adaptive and Generalizable Time Series Foundation Models

Attention Localization Through Separator Tokens: Unlocking Long Numerical Sequence Processing in LLMs

Automated Random Embedding for Practical Bayesian Optimization with Unknown Effective Dimension

Xihe: Scalable Zero-shot Time Series Learner via Hierarchical Interleaved Block Attention

Useless, or Untapped? Unlocking the Full Value of Zero-Advantage Samples for Better Policy Optimization

LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch

Relation Augmented Preferential Bayesian Optimization via Preference Propagation