15 citations · 36 across the 5 of their papers we have counts for
6 papers · 1 filter
Grid2Matrix: Revealing Digital Agnosia in Vision-Language Models
Yunkai Zhang, Linda Li, Yingxin Cui +5
Vision-Language Models (VLMs) excel on many multimodal reasoning benchmarks, but these evaluations often do not require an exhaustive readout of the image and can therefore obscure…
VideoGLUE: Video General Understanding Evaluation of Foundation Models
Liangzhe Yuan, Nitesh Bharadwaj Gundavarapu, Long Zhao +14
We evaluate the video understanding capabilities of existing foundation models (FMs) using a carefully designed experiment protocol consisting of three hallmark tasks (action recog…
Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception
Hassan Akbari, Dan Kondratyuk, Yin Cui +3
We present Integrated Multimodal Perception (IMP), a simple and scalable multimodal multi-task training and modeling approach. IMP integrates multimodal inputs including image, vid…
Unified Visual Relationship Detection with Vision and Language Models
Long Zhao, Liangzhe Yuan, Boqing Gong +5
This work focuses on training a single visual relationship detector predicting over the union of label spaces from multiple datasets. Merging labels spanning different datasets cou…
Revisiting 3D ResNets for Video Recognition
Xianzhi Du, Yeqing Li, Yin Cui +3
A recent work from Bello shows that training and scaling strategies may be more significant than model architectures for visual recognition. This short note studies effective train…
Federated Multi-Target Domain Adaptation
Chun-Han Yao, Boqing Gong, Yin Cui +3
Federated learning methods enable us to train machine learning models on distributed user data while preserving its privacy. However, it is not always feasible to obtain high-quali…