85 citations · 230 across the 7 of their papers we have counts for
9 papers · 1 filter
MViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design
Hanxue Liang, Zhiwen Fan, Rishov Sarkar +6
Multi-task learning (MTL) encapsulates multiple learned tasks in a single model and often lets those tasks learn better jointly. However, when deploying MTL onto those real-world s…
VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation
Linjie Li, Jie Lei, Zhe Gan +12
Most existing video-and-language (VidL) research focuses on a single dataset, or multiple datasets of a single task. In reality, a truly useful VidL system is expected to be easily…
Chasing Sparsity in Vision Transformers: An End-to-End Exploration
Tianlong Chen, Yu Cheng, Zhe Gan +3
Vision transformers (ViTs) have recently received explosive popularity, but their enormous model sizes and training costs remain daunting. Conventional post-training pruning often…
CUPID: Adaptive Curation of Pre-training Data for Video-and-Language Representation Learning
Luowei Zhou, Jingjing Liu, Yu Cheng +2
This work concerns video-language pre-training and representation learning. In this now ubiquitous training scheme, a model first performs pre-training on paired videos and text (e…
UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training
Mingyang Zhou, Luowei Zhou, Shuohang Wang +4
Vision-and-language pre-training has achieved impressive success in learning multimodal representations between vision and language. To generalize this success to non-English langu…
The Elastic Lottery Ticket Hypothesis
Xiaohan Chen, Yu Cheng, Shuohang Wang +3
Lottery Ticket Hypothesis (LTH) raises keen attention to identifying sparse trainable subnetworks, or winning tickets, which can be trained in isolation to achieve similar or even…