128 citations · 380 across the 15 of their papers we have counts for
4 papers · 1 filter
VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding
Hu Xu, Gargi Ghosh, Po-Yao Huang +5
We present VideoCLIP, a contrastive approach to pre-train a unified model for zero-shot video and text understanding, without using any labels on downstream tasks. VideoCLIP trains…
HTLM: Hyper-Text Pre-Training and Prompting of Language Models
Armen Aghajanyan, Dmytro Okhonko, Mike Lewis +4
We introduce HTLM, a hyper-text language model trained on a large-scale web crawl. Modeling hyper-text has a number of advantages: (1) it is easily gathered at scale, (2) it provid…
VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding
Hu Xu, Gargi Ghosh, Po-Yao Huang +5
We present a simplified, task-agnostic multi-modal pre-training approach that can accept either video or text input, or both for a variety of end tasks. Existing pre-training are t…
Multi-task Retrieval for Knowledge-Intensive Tasks
Jean Maillard, Vladimir Karpukhin, Fabio Petroni +4
Retrieving relevant contexts from a large corpus is a crucial step for tasks such as open-domain question answering and fact checking. Although neural retrieval outperforms traditi…