Oral AI Applications

SeeA* enhances A* search by selectively sampling promising nodes, improving exploration and efficiency, especially with less accurate heuristics.

RL-GPT seamlessly integrates Large Language Models (LLMs) and Reinforcement Learning (RL) to create highly efficient agents mastering complex tasks in open-world environments.

SDF-Sim: A novel learned rigid-body simulator that leverages SDFs to achieve unprecedented scalability, enabling simulations with hundreds of objects and millions of nodes.

Boost AI predictions by using human judgment on algorithmically indistinguishable inputs!

Graph Diffusion Transformer (Graph DiT) masters multi-conditional molecular generation by cleverly integrating property representations into a graph-dependent noise model, achieving superior performan…

CMuST: a novel continuous multi-task spatiotemporal learning framework tackles urban data limitations by enabling cross-interactions and task-level cooperation for enhanced generalization and adaptabi…

Boosting preference learning, this research uses human response times to improve linear bandit algorithms, significantly accelerating preference identification.