most citedVideo-Holmes: Can MLLM Think Like Holmes for Complex Video Reasoning?

1 citations · 2 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2025

ARC-Chapter: Structuring Hour-Long Videos into Navigable Chapters and Hierarchical Summaries

Junfu Pu, Teng Wang, Yixiao Ge +3

The proliferation of hour-long videos (e.g., lectures, podcasts, documentaries) has intensified demand for efficient content structuring. However, existing approaches are constrain…

cs.CL2025

From Denoising to Refining: A Corrective Framework for Vision-Language Diffusion Model

Yatai Ji, Teng Wang, Yuying Ge +4

Discrete diffusion models have emerged as a promising direction for vision-language tasks, offering bidirectional context modeling and theoretical parallelization. However, their p…

cs.CV2025

AudioStory: Generating Long-Form Narrative Audio with Large Language Models

Yuxin Guo, Teng Wang, Yuying Ge +4

Recent advances in text-to-audio (TTA) generation excel at synthesizing short audio clips but struggle with long-form narrative audio, which requires temporal coherence and composi…

cs.CV20251 cited

ARC-Hunyuan-Video-7B: Structured Video Comprehension of Real-World Shorts

Yuying Ge, Yixiao Ge, Chen Li +15

Real-world user-generated short videos, especially those distributed on platforms such as WeChat Channel and TikTok, dominate the mobile internet. However, current large multimodal…

cs.CV20251 cited

Video-Holmes: Can MLLM Think Like Holmes for Complex Video Reasoning?

Junhao Cheng, Yuying Ge, Teng Wang +3

Recent advances in CoT reasoning and RL post-training have been reported to enhance video reasoning capabilities of MLLMs. This progress naturally raises a question: can these mode…

cs.CV2025

GenHancer: Imperfect Generative Models are Secretly Strong Vision-Centric Enhancers

Shijie Ma, Yuying Ge, Teng Wang +3

The synergy between generative and discriminative models receives growing attention. While discriminative Contrastive Language-Image Pre-Training (CLIP) excels in high-level semant…