3 papers
cs.CV2025
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…
cs.CV2025
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…
cs.CV2025
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…