activity
20232026
most citedMMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI

16 citations · 28 across the 25 of their papers we have counts for

collaborators
Showing 2025Show all

7 papers · 1 filter

cs.CV2025

Visual-Aware CoT: Achieving High-Fidelity Visual Consistency in Unified Models

Zixuan Ye, Quande Liu, Cong Wei +5

Recently, the introduction of Chain-of-Thought (CoT) has largely improved the generation ability of unified models. However, it is observed that the current thinking process during…

cs.CV2025

UFVideo: Towards Unified Fine-Grained Video Cooperative Understanding with Large Language Models

Hewen Pan, Cong Wei, Dashuang Liang +8

With the advancement of multi-modal Large Language Models (LLMs), Video LLMs have been further developed to perform on holistic and specialized video understanding. However, existi…

cs.CV2025

UniVideo: Unified Understanding, Generation, and Editing for Videos

Cong Wei, Quande Liu, Zixuan Ye +5

Unified multimodal models have shown promising results in multimodal content generation and editing but remain largely limited to the image domain. In this work, we present UniVide…

cs.CV2025

Advancing Visual Large Language Model for Multi-granular Versatile Perception

Wentao Xiang, Haoxian Tan, Cong Wei +3

Perception is a fundamental task in the field of computer vision, encompassing a diverse set of subtasks that can be systematically categorized into four distinct groups based on t…

cs.CV2025

MoCha: Towards Movie-Grade Talking Character Synthesis

Cong Wei, Bo Sun, Haoyu Ma +10

Recent advancements in video generation have achieved impressive motion realism, yet they often overlook character-driven storytelling, a crucial task for automated film, animation…

cs.CV2025

Vamba: Understanding Hour-Long Videos with Hybrid Mamba-Transformers

Weiming Ren, Wentao Ma, Huan Yang +3

State-of-the-art transformer-based large multimodal models (LMMs) struggle to handle hour-long video inputs due to the quadratic complexity of the causal self-attention operations,…

cs.LG2025

A Survey on Data-Centric AI: Tabular Learning from Reinforcement Learning and Generative AI Perspective

Wangyang Ying, Cong Wei, Nanxu Gong +7

Tabular data is one of the most widely used data formats across various domains such as bioinformatics, healthcare, and marketing. As artificial intelligence moves towards a data-c…