1 citations · 1 across the 5 of their papers we have counts for
5 papers
ReAlign: Optimizing the Visual Document Retriever with Reasoning-Guided Fine-Grained Alignment
Hao Yang, Yifan Ji, Zhipeng Xu +6
Visual document retrieval aims to retrieve a set of document pages relevant to a query from visually rich collections. Existing methods often employ Vision-Language Models (VLMs) t…
Omni-Video 2: Scaling MLLM-Conditioned Diffusion for Unified Video Generation and Editing
Hao Yang, Zhiyu Tan, Jia Gong +7
We present Omni-Video 2, a scalable and computationally efficient model that connects pretrained multimodal large-language models (MLLMs) with video diffusion models for unified vi…
Omni-Video: Democratizing Unified Video Understanding and Generation
Zhiyu Tan, Hao Yang, Luozheng Qin +3
Notable breakthroughs in unified understanding and generation modeling have led to remarkable advancements in image understanding, reasoning, production and editing, yet current fo…
Raccoon: Multi-stage Diffusion Training with Coarse-to-Fine Curating Videos
Zhiyu Tan, Junyan Wang, Hao Yang +4
Text-to-video generation has demonstrated promising progress with the advent of diffusion models, yet existing approaches are limited by dataset quality and computational resources…
An Empirical Study and Analysis of Text-to-Image Generation Using Large Language Model-Powered Textual Representation
Zhiyu Tan, Mengping Yang, Luozheng Qin +5
One critical prerequisite for faithful text-to-image generation is the accurate understanding of text inputs. Existing methods leverage the text encoder of the CLIP model to repres…