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cs.CV2026

PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance

Shangkun Sun, Ruyang Liu, Haoran Tang +5

In the past year, video-based large language models (Video LLMs) have achieved impressive progress, particularly in their ability to process long videos through extremely extended…

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.CV2025

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.CV2025

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Yuying Ge, Sijie Zhao, Jinguo Zhu +6

The rapid evolution of multimodal foundation model has demonstrated significant progresses in vision-language understanding and generation, e.g., our previous work SEED-LLaMA. Howe…

cs.CV2024

BT-Adapter: Video Conversation is Feasible Without Video Instruction Tuning

Ruyang Liu, Chen Li, Yixiao Ge +3

The recent progress in Large Language Models (LLM) has spurred various advancements in image-language conversation agents, while how to build a proficient video-based dialogue syst…

cs.CV2024

SEED-Data-Edit Technical Report: A Hybrid Dataset for Instructional Image Editing

Yuying Ge, Sijie Zhao, Chen Li +2

In this technical report, we introduce SEED-Data-Edit: a unique hybrid dataset for instruction-guided image editing, which aims to facilitate image manipulation using open-form lan…