630 citations · 2.3k across the 48 of their papers we have counts for
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Aligning Large Multimodal Models with Factually Augmented RLHF
Zhiqing Sun, Sheng Shen, Shengcao Cao +9
Large Multimodal Models (LMM) are built across modalities and the misalignment between two modalities can result in "hallucination", generating textual outputs that are not grounde…
LLM-grounded Video Diffusion Models
Long Lian, Baifeng Shi, Adam Yala +2
Text-conditioned diffusion models have emerged as a promising tool for neural video generation. However, current models still struggle with intricate spatiotemporal prompts and oft…
VideoCutLER: Surprisingly Simple Unsupervised Video Instance Segmentation
Xudong Wang, Ishan Misra, Ziyun Zeng +2
Existing approaches to unsupervised video instance segmentation typically rely on motion estimates and experience difficulties tracking small or divergent motions. We present Video…
Stochastic positional embeddings improve masked image modeling
Amir Bar, Florian Bordes, Assaf Shocher +6
Masked Image Modeling (MIM) is a promising self-supervised learning approach that enables learning from unlabeled images. Despite its recent success, learning good representations…
Hierarchical Open-vocabulary Universal Image Segmentation
Xudong Wang, Shufan Li, Konstantinos Kallidromitis +3
Open-vocabulary image segmentation aims to partition an image into semantic regions according to arbitrary text descriptions. However, complex visual scenes can be naturally decomp…