6 papers · 1 filter
PhyGround: Benchmarking Physical Reasoning in Generative World Models
Juyi Lin, Arash Akbari, Yumei He +13
Generative world models are increasingly used for video generation, where learned simulators are expected to capture the physical rules that govern real-world dynamics. However, ev…
AgentMV: A State-Guided Multi-Agent Framework for Budget-Aware Music Video Generation
Huimin Wang, Chang Xia, Leilei Ouyang +3
Generating a complete music video from a song requires more than synthesizing visually plausible clips for individual lyric prompts. A practical system must maintain long-range vis…
ThinkJEPA: Empowering Latent World Models with Large Vision-Language Reasoning Model
Haichao Zhang, Yijiang Li, Shwai He +5
Recent progress in latent world models (e.g., V-JEPA2) has shown promising capability in forecasting future world states from video observations. Nevertheless, dense prediction fro…
LinkedOut: Linking World Knowledge Representation Out of Video LLM for Next-Generation Video Recommendation
Haichao Zhang, Yao Lu, Lichen Wang +4
Video Large Language Models (VLLMs) unlock world-knowledge-aware video understanding through pretraining on internet-scale data and have already shown promise on tasks such as movi…
Dense Video Understanding with Gated Residual Tokenization
Haichao Zhang, Wenhao Chai, Shwai He +2
High temporal resolution is essential for capturing fine-grained details in video understanding. However, current video large language models (VLLMs) and benchmarks mostly rely on…
VQToken: Neural Discrete Token Representation Learning for Extreme Token Reduction in Video Large Language Models
Haichao Zhang, Yun Fu
Token-based video representation has emerged as a promising approach for enabling large language models (LLMs) to interpret video content. However, existing token reduction techniq…