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20242026
most citedOvis: Structural Embedding Alignment for Multimodal Large Language Model

4 citations · 10 across the 29 of their papers we have counts for

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18 papers · 1 filter

cs.CV2026

Efficient Scene-Text Refinement via Pixel-Space Grouped Image Generation

Yaoli Liu, Guo-Hua Wang, Yiyang Chen +4

Generated images often have coherent layouts and visual content, yet local errors in small text and complex characters still limit their readability and practical use. Scene-text r…

cs.CV2026

OvisOCR2 Technical Report

Shiyin Lu, Yinglun Li, Yu Xia +10

We introduce OvisOCR2, a 0.8B document parsing model. OvisOCR2 is designed as an end-to-end parser: given a document page image, it generates a Markdown representation in natural r…

cs.CV2026

Walk the Talk: Bridging the Reasoning-Action Gap for Thinking with Images via Multimodal Agentic Policy Optimization

Wenhao Yang, Yu Xia, Jinlong Huang +10

Recent advancements in Multimodal Large Language Models (MLLMs) have incentivized models to ``think with images'' by actively invoking visual tools during multi-turn reasoning. The…

cs.CV2026

M: Dual-Memory Augmentation for Long-Horizon Web Agents via Trajectory Summarization and Insight Retrieval

Dawei Yan, Haokui Zhang, Guangda Huzhang +8

Multimodal Large Language Models (MLLMs) based agents have demonstrated remarkable potential in autonomous web navigation. However, handling long-horizon tasks remains a critical b…

cs.CV2026

Vectra: A New Metric, Dataset, and Model for Visual Quality Assessment in E-Commerce In-Image Machine Translation

Qingyu Wu, Yuxuan Han, Haijun Li +5

In-Image Machine Translation (IIMT) powers cross-border e-commerce product listings; existing research focuses on machine translation evaluation, while visual rendering quality is…

cs.CV2026

Text is All You Need for Vision-Language Model Jailbreaking

Yihang Chen, Zhao Xu, Youyuan Jiang +2

Large Vision-Language Models (LVLMs) are increasingly equipped with robust safety safeguards to prevent responses to harmful or disallowed prompts. However, these defenses often fo…

cs.CV2026

Deep But Reliable: Advancing Multi-turn Reasoning for Thinking with Images

Wenhao Yang, Yu Xia, Jinlong Huang +7

Recent advances in large Vision-Language Models (VLMs) have exhibited strong reasoning capabilities on complex visual tasks by thinking with images in their Chain-of-Thought (CoT),…

cs.CV2025

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…

cs.CV2025

Towards Efficient VLMs: Information-Theoretic Driven Compression via Adaptive Structural Pruning

Zhaoqi Xu, Yingying Zhang, Jian Li +3

Recent advances in vision-language models (VLMs) have shown remarkable performance across multimodal tasks, yet their ever-growing scale poses severe challenges for deployment and…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025★ 2 cited

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

UNIC-Adapter: Unified Image-instruction Adapter with Multi-modal Transformer for Image Generation

Lunhao Duan, Shanshan Zhao, Wenjun Yan +7

Recently, text-to-image generation models have achieved remarkable advancements, particularly with diffusion models facilitating high-quality image synthesis from textual descripti…

cs.CV2024★ 4 cited

Ovis: Structural Embedding Alignment for Multimodal Large Language Model

Shiyin Lu, Yang Li, Qing-Guo Chen +4

Current Multimodal Large Language Models (MLLMs) typically integrate a pre-trained LLM with another pre-trained vision transformer through a connector, such as an MLP, endowing the…

cs.CV2024★ 1 cited

Parrot: Multilingual Visual Instruction Tuning

Hai-Long Sun, Da-Wei Zhou, Yang Li +8

The rapid development of Multimodal Large Language Models (MLLMs), such as GPT-4o, marks a significant step toward artificial general intelligence. Existing methods typically align…