33 citations · 36 across the 2 of their papers we have counts for
5 papers
VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learning
Hao Tan, Jie Lei, Thomas Wolf +1
Video understanding relies on perceiving the global content and modeling its internal connections (e.g., causality, movement, and spatio-temporal correspondence). To learn these in…
Unifying Vision-and-Language Tasks via Text Generation
Jaemin Cho, Jie Lei, Hao Tan +1
Existing methods for vision-and-language learning typically require designing task-specific architectures and objectives for each task. For example, a multi-label answer classifier…
ArraMon: A Joint Navigation-Assembly Instruction Interpretation Task in Dynamic Environments
Hyounghun Kim, Abhay Zala, Graham Burri +2
For embodied agents, navigation is an important ability but not an isolated goal. Agents are also expected to perform specific tasks after reaching the target location, such as pic…
Vokenization: Improving Language Understanding with Contextualized, Visual-Grounded Supervision
Hao Tan, Mohit Bansal
Humans learn language by listening, speaking, writing, reading, and also, via interaction with the multimodal real world. Existing language pre-training frameworks show the effecti…
MAF: Multimodal Alignment Framework for Weakly-Supervised Phrase Grounding
Qinxin Wang, Hao Tan, Sheng Shen +2
Phrase localization is a task that studies the mapping from textual phrases to regions of an image. Given difficulties in annotating phrase-to-object datasets at scale, we develop…