52 citations · 139 across the 17 of their papers we have counts for
4 papers · 1 filter
CoDi-2: In-Context, Interleaved, and Interactive Any-to-Any Generation
Zineng Tang, Ziyi Yang, Mahmoud Khademi +3
We present CoDi-2, a versatile and interactive Multimodal Large Language Model (MLLM) that can follow complex multimodal interleaved instructions, conduct in-context learning (ICL)…
Any-to-Any Generation via Composable Diffusion
Zineng Tang, Ziyi Yang, Chenguang Zhu +2
We present Composable Diffusion (CoDi), a novel generative model capable of generating any combination of output modalities, such as language, image, video, or audio, from any comb…
Unifying Vision, Text, and Layout for Universal Document Processing
Zineng Tang, Ziyi Yang, Guoxin Wang +6
We propose Universal Document Processing (UDOP), a foundation Document AI model which unifies text, image, and layout modalities together with varied task formats, including docume…
Language Models with Image Descriptors are Strong Few-Shot Video-Language Learners
Zhenhailong Wang, Manling Li, Ruochen Xu +10
The goal of this work is to build flexible video-language models that can generalize to various video-to-text tasks from few examples, such as domain-specific captioning, question…