4 citations · 10 across the 23 of their papers we have counts for
13 papers · 1 filter
SPACE: Noise Contrastive Estimation Stabilizes Self-Play Fine-Tuning for Large Language Models
Yibo Wang, Qing-Guo Chen, Zhao Xu +3
Self-play fine-tuning has demonstrated promising abilities in adapting large language models (LLMs) to downstream tasks with limited real-world data. The basic principle is to iter…
Diffusion-SDPO: Safeguarded Direct Preference Optimization for Diffusion Models
Minghao Fu, Guo-Hua Wang, Tianyu Cui +4
Text-to-image diffusion models deliver high-quality images, yet aligning them with human preferences remains challenging. We revisit diffusion-based Direct Preference Optimization…
Ovis-Image Technical Report
Guo-Hua Wang, Liangfu Cao, Tianyu Cui +8
We introduce , a 7B text-to-image model specifically optimized for high-quality text rendering, designed to operate efficiently under stringent computational c…
Omni-View: Unlocking How Generation Facilitates Understanding in Unified 3D Model based on Multiview images
JiaKui Hu, Shanshan Zhao, Qing-Guo Chen +6
This paper presents Omni-View, which extends the unified multimodal understanding and generation to 3D scenes based on multiview images, exploring the principle that "generation fa…
Scaling Beyond Context: A Survey of Multimodal Retrieval-Augmented Generation for Document Understanding
Sensen Gao, Shanshan Zhao, Xu Jiang +7
Document understanding is critical for applications from financial analysis to scientific discovery. Current approaches, whether OCR-based pipelines feeding Large Language Models (…
TeEFusion: Blending Text Embeddings to Distill Classifier-Free Guidance
Minghao Fu, Guo-Hua Wang, Xiaohao Chen +4
Recent advances in text-to-image synthesis largely benefit from sophisticated sampling strategies and classifier-free guidance (CFG) to ensure high-quality generation. However, CFG…
Ovis-U1 Technical Report
Guo-Hua Wang, Shanshan Zhao, Xinjie Zhang +9
In this report, we introduce Ovis-U1, a 3-billion-parameter unified model that integrates multimodal understanding, text-to-image generation, and image editing capabilities. Buildi…
Multimodal Tabular Reasoning with Privileged Structured Information
Jun-Peng Jiang, Yu Xia, Hai-Long Sun +6
Tabular reasoning involves multi-step information extraction and logical inference over tabular data. While recent advances have leveraged large language models (LLMs) for reasonin…
Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunities
Shanshan Zhao, Xinjie Zhang, Jintao Guo +9
Recent years have seen remarkable progress in both multimodal understanding models and image generation models. Despite their respective successes, these two domains have evolved i…
MMCR: Advancing Visual Language Model in Multimodal Multi-Turn Contextual Reasoning
Dawei Yan, Yang Li, Qing-Guo Chen +4
Compared to single-turn dialogue, multi-turn dialogue involving multiple images better aligns with the needs of real-world human-AI interactions. Additionally, as training data, it…
CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image Generation
Minghao Fu, Guo-Hua Wang, Liangfu Cao +4
Diffusion models have emerged as a dominant approach for text-to-image generation. Key components such as the human preference alignment and classifier-free guidance play a crucial…
Evaluating Image Caption via Cycle-consistent Text-to-Image Generation
Tianyu Cui, Jinbin Bai, Guo-Hua Wang +5
Evaluating image captions typically relies on reference captions, which are costly to obtain and exhibit significant diversity and subjectivity. While reference-free evaluation met…
MDP3: A Training-free Approach for List-wise Frame Selection in Video-LLMs
Hui Sun, Shiyin Lu, Huanyu Wang +5
Video large language models (Video-LLMs) have made significant progress in understanding videos. However, processing multiple frames leads to lengthy visual token sequences, presen…