342 citations · 2k across the 44 of their papers we have counts for
45 papers
Towards Understanding Graphical Perception in Large Multimodal Models
Kai Zhang, Jianwei Yang, Jeevana Priya Inala +4
Despite the promising results of large multimodal models (LMMs) in complex vision-language tasks that require knowledge, reasoning, and perception abilities together, we surprising…
Simplifying DINO via Coding Rate Regularization
Ziyang Wu, Jingyuan Zhang, Druv Pai +5
DINO and DINOv2 are two model families being widely used to learn representations from unlabeled imagery data at large scales. Their learned representations often enable state-of-t…
Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth Fusion
Jiuhai Chen, Jianwei Yang, Haiping Wu +4
We present Florence-VL, a new family of multimodal large language models (MLLMs) with enriched visual representations produced by Florence-2, a generative vision foundation model.…
DeepStack: Deeply Stacking Visual Tokens is Surprisingly Simple and Effective for LMMs
Lingchen Meng, Jianwei Yang, Rui Tian +4
Most large multimodal models (LMMs) are implemented by feeding visual tokens as a sequence into the first layer of a large language model (LLM). The resulting architecture is simpl…
BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once
Theodore Zhao, Yu Gu, Jianwei Yang +12
Biomedical image analysis is fundamental for biomedical discovery in cell biology, pathology, radiology, and many other biomedical domains. Holistic image analysis comprises interd…
Matryoshka Multimodal Models
Mu Cai, Jianwei Yang, Jianfeng Gao +1
Large Multimodal Models (LMMs) such as LLaVA have shown strong performance in visual-linguistic reasoning. These models first embed images into a fixed large number of visual token…
Pix2Gif: Motion-Guided Diffusion for GIF Generation
Hitesh Kandala, Jianfeng Gao, Jianwei Yang
We present Pix2Gif, a motion-guided diffusion model for image-to-GIF (video) generation. We tackle this problem differently by formulating the task as an image translation problem…
Towards a clinically accessible radiology foundation model: open-access and lightweight, with automated evaluation
Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu +24
The scaling laws and extraordinary performance of large foundation models motivate the development and utilization of such models in biomedicine. However, despite early promising r…
Foundation Models for Biomedical Image Segmentation: A Survey
Ho Hin Lee, Yu Gu, Theodore Zhao +9
Recent advancements in biomedical image analysis have been significantly driven by the Segment Anything Model (SAM). This transformative technology, originally developed for genera…
VCoder: Versatile Vision Encoders for Multimodal Large Language Models
Jitesh Jain, Jianwei Yang, Humphrey Shi
Humans possess the remarkable skill of Visual Perception, the ability to see and understand the seen, helping them make sense of the visual world and, in turn, reason. Multimodal L…
LLaVA-Grounding: Grounded Visual Chat with Large Multimodal Models
Hao Zhang, Hongyang Li, Feng Li +8
With the recent significant advancements in large multi-modal models (LMMs), the importance of their grounding capability in visual chat is increasingly recognized. Despite recent…
IMProv: Inpainting-based Multimodal Prompting for Computer Vision Tasks
Jiarui Xu, Yossi Gandelsman, Amir Bar +4
In-context learning allows adapting a model to new tasks given a task description at test time. In this paper, we present IMProv - a generative model that is able to in-context lea…
Visual In-Context Prompting
Feng Li, Qing Jiang, Hao Zhang +9
In-context prompting in large language models (LLMs) has become a prevalent approach to improve zero-shot capabilities, but this idea is less explored in the vision domain. Existin…
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Shilong Liu, Hao Cheng, Haotian Liu +10
LLaVA-Plus is a general-purpose multimodal assistant that expands the capabilities of large multimodal models. It maintains a skill repository of pre-trained vision and vision-lang…
Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V
Jianwei Yang, Hao Zhang, Feng Li +3
We present Set-of-Mark (SoM), a new visual prompting method, to unleash the visual grounding abilities of large multimodal models (LMMs), such as GPT-4V. As illustrated in Fig. 1 (…
LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing
Wei-Ge Chen, Irina Spiridonova, Jianwei Yang +2
LLaVA-Interactive is a research prototype for multimodal human-AI interaction. The system can have multi-turn dialogues with human users by taking multimodal user inputs and genera…
BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys
Yu Gu, Jianwei Yang, Naoto Usuyama +5
Rapid progress has been made in instruction-learning for image editing with natural-language instruction, as exemplified by InstructPix2Pix. In biomedicine, such methods can be app…
Multimodal Foundation Models: From Specialists to General-Purpose Assistants
Chunyuan Li, Zhe Gan, Zhengyuan Yang +4
This paper presents a comprehensive survey of the taxonomy and evolution of multimodal foundation models that demonstrate vision and vision-language capabilities, focusing on the t…
An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models
Yadong Lu, Chunyuan Li, Haotian Liu +3
Visual instruction tuning has recently shown encouraging progress with open-source large multimodal models (LMM) such as LLaVA and MiniGPT-4. However, most existing studies of open…
Semantic-SAM: Segment and Recognize Anything at Any Granularity
Feng Li, Hao Zhang, Peize Sun +6
In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity. Our model offers two key advanta…
detrex: Benchmarking Detection Transformers
Tianhe Ren, Shilong Liu, Feng Li +13
The DEtection TRansformer (DETR) algorithm has received considerable attention in the research community and is gradually emerging as a mainstream approach for object detection and…
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day
Chunyuan Li, Cliff Wong, Sheng Zhang +6
Conversational generative AI has demonstrated remarkable promise for empowering biomedical practitioners, but current investigations focus on unimodal text. Multimodal conversation…
A Strong and Reproducible Object Detector with Only Public Datasets
Tianhe Ren, Jianwei Yang, Shilong Liu +6
This work presents Focal-Stable-DINO, a strong and reproducible object detection model which achieves 64.6 AP on COCO val2017 and 64.8 AP on COCO test-dev using only 700M parameter…
Segment Everything Everywhere All at Once
Xueyan Zou, Jianwei Yang, Hao Zhang +6
In this work, we present SEEM, a promptable and interactive model for segmenting everything everywhere all at once in an image, as shown in Fig.1. In SEEM, we propose a novel decod…