most citedSet-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V

25 citations · 58 across the 7 of their papers we have counts for

collaborators

14 papers

cs.CV2024

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.…

cs.CV2024

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…

cs.CV2024

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…

cs.CL2024

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…

cs.CL2024

Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries

Zelalem Gero, Chandan Singh, Yiqing Xie +6

Summarizing clinical text is crucial in health decision-support and clinical research. Large language models (LLMs) have shown the potential to generate accurate clinical text summ…

cs.CL2024

TrustLLM: Trustworthiness in Large Language Models

Yue Huang, Lichao Sun, Haoran Wang +67

Large language models (LLMs), exemplified by ChatGPT, have gained considerable attention for their excellent natural language processing capabilities. Nonetheless, these LLMs prese…