Xiao Xu

Multi-modal models can now better handle distribution shifts thanks to a new method that explicitly models how different categories are distributed, even when the modalities are asymmetrical.

VLAs can learn to adapt to new environments at test time without any fine-tuning, achieving significant performance gains on robotic manipulation and Atari games.

Representing combinatorial treatments with permutation-invariant embeddings boosts uplift estimation accuracy and stability, especially for rare policies.