8 citations · 42 across the 24 of their papers we have counts for
6 papers · 1 filter
Video Event Extraction via Tracking Visual States of Arguments
Guang Yang, Manling Li, Jiajie Zhang +3
Video event extraction aims to detect salient events from a video and identify the arguments for each event as well as their semantic roles. Existing methods focus on capturing the…
ADEPT: A DEbiasing PrompT Framework
Ke Yang, Charles Yu, Yi Fung +2
Several works have proven that finetuning is an applicable approach for debiasing contextualized word embeddings. Similarly, discrete prompts with semantic meanings have shown to b…
Learning to Decompose Visual Features with Latent Textual Prompts
Feng Wang, Manling Li, Xudong Lin +3
Recent advances in pre-training vision-language models like CLIP have shown great potential in learning transferable visual representations. Nonetheless, for downstream inference,…
Multimedia Generative Script Learning for Task Planning
Qingyun Wang, Manling Li, Hou Pong Chan +4
Goal-oriented generative script learning aims to generate subsequent steps to reach a particular goal, which is an essential task to assist robots or humans in performing stereotyp…
Towards Fast Adaptation of Pretrained Contrastive Models for Multi-channel Video-Language Retrieval
Xudong Lin, Simran Tiwari, Shiyuan Huang +4
Multi-channel video-language retrieval require models to understand information from different channels (e.g. videoquestion, videospeech) to correctly link a video with a tex…
Rethinking Task Sampling for Few-shot Vision-Language Transfer Learning
Zhenhailong Wang, Hang Yu, Manling Li +2
Despite achieving state-of-the-art zero-shot performance, existing vision-language models still fall short of few-shot transfer ability on domain-specific problems. Classical fine-…