14 citations · 26 across the 6 of their papers we have counts for
6 papers
Time-Frequency Geometric Cross-Attention for Chunked Vision-Language-Action Models
Shengye Dong, Haochen Niu, Hao Liu +3
Modern vision-language-action (VLA) policies predict a whole chunk of actions: one to two seconds of coordinated motion emitted in a single forward pass. Yet an action chunk is ess…
ElasticTok: Adaptive Tokenization for Image and Video
Wilson Yan, Volodymyr Mnih, Aleksandra Faust +3
Efficient video tokenization remains a key bottleneck in learning general purpose vision models that are capable of processing long video sequences. Prevailing approaches are restr…
World Model on Million-Length Video And Language With Blockwise RingAttention
Hao Liu, Wilson Yan, Matei Zaharia +1
Enabling long-context understanding remains a key challenge in scaling existing sequence models -- a crucial component in developing generally intelligent models that can process a…
Ring Attention with Blockwise Transformers for Near-Infinite Context
Hao Liu, Matei Zaharia, Pieter Abbeel
Transformers have emerged as the architecture of choice for many state-of-the-art AI models, showcasing exceptional performance across a wide range of AI applications. However, the…
Exploration with Principles for Diverse AI Supervision
Hao Liu, Matei Zaharia, Pieter Abbeel
Training large transformers using next-token prediction has given rise to groundbreaking advancements in AI. While this generative AI approach has produced impressive results, it h…
The Power of the Senses: Generalizable Manipulation from Vision and Touch through Masked Multimodal Learning
Carmelo Sferrazza, Younggyo Seo, Hao Liu +2
Humans rely on the synergy of their senses for most essential tasks. For tasks requiring object manipulation, we seamlessly and effectively exploit the complementarity of our sense…