Skip to content
VuFind
  • Login
    • English
    • Deutsch
    • Español
    • Français
    • Italiano
    • 日本語
    • Nederlands
    • Português
    • Português (Brasil)
    • 中文(简体)
    • 中文(繁體)
    • Türkçe
    • עברית
    • Gaeilge
    • Cymraeg
    • Ελληνικά
    • Català
    • Euskara
    • Русский
    • Čeština
    • Suomi
    • Svenska
    • polski
    • Dansk
    • slovenščina
    • اللغة العربية
    • বাংলা
    • Galego
    • Tiếng Việt
    • Hrvatski
    • हिंदी
    • Հայերէն
    • Українська
    • Sámegiella
    • Монгол
    • Māori
Advanced
  • Cite this
  • Text this
  • Email this
  • Print
  • Export Record
    • Export to RefWorks
    • Export to EndNoteWeb
    • Export to EndNote
  • Save to List
  • Permanent link
Cover Image

Saved in:
Bibliographic Details
Main Authors: Shi, Yang, Wang, Huanqian, Xie, Wulin, Zhang, Huanyao, Zhao, Lijie, Zhang, Yi-Fan, Li, Xinfeng, Fu, Chaoyou, Wen, Zhuoer, Liu, Wenting, Zhang, Zhuoran, Chen, Xinlong, Zeng, Bohan, Yang, Sihan, Guan, Yushuo, Zhang, Zhang, Wang, Liang, Li, Haoxuan, Lin, Zhouchen, Zhang, Yuanxing, Wan, Pengfei, Wang, Haotian, Yang, Wenjing
Format: Preprint
Published: 2025
Subjects:
Computer Vision and Pattern Recognition
Online Access:https://arxiv.org/abs/2505.21333
Tags: Add Tag
No Tags, Be the first to tag this record!
  • Holdings
  • Description
  • Table of Contents
  • Comments
  • Similar Items
  • Staff View

Internet

https://arxiv.org/abs/2505.21333

Similar Items

  • MME-Unify: A Comprehensive Benchmark for Unified Multimodal Understanding and Generation Models
    by: Xie, Wulin, et al.
    Published: (2025)
  • Mavors: Multi-granularity Video Representation for Multimodal Large Language Model
    by: Shi, Yang, et al.
    Published: (2025)
  • VidBridge-R1: Bridging QA and Captioning for RL-based Video Understanding Models with Intermediate Proxy Tasks
    by: Chen, Xinlong, et al.
    Published: (2025)
  • The Unseen Bias: How Norm Discrepancy in Pre-Norm MLLMs Leads to Visual Information Loss
    by: Li, Bozhou, et al.
    Published: (2025)
  • GRAN-TED: Generating Robust, Aligned, and Nuanced Text Embedding for Diffusion Models
    by: Li, Bozhou, et al.
    Published: (2025)

Search Options

  • Search History
  • Advanced Search

Find More

  • Browse the Catalog
  • Browse Alphabetically
  • Explore Channels
  • Course Reserves
  • New Items

Need Help?

  • Search Tips
  • Ask a Librarian
  • FAQs