4 papers
MatchLM2Lite: A Scalable MLLM-to-Lite Framework for Reproduced Content Identification
Xiaotian Fan, Hiok Hian Ong, David Yuchen Wang +3
Content moderation is critical for online video platforms to ensure content safety, protect creators, and sustain positive user experiences. Beyond filtering harmful content, platf…
MLT-Dedup: Efficient Large-Scale Online Video Deduplication via Multi-Level Representations and Spatial-Temporal Matching
David Yuchen Wang, Haoying Li, Hailun Xu +6
The explosive growth of user-generated video content on online platforms is accompanied by the emergence of numerous near-duplicate videos--videos that are identical or highly simi…
FOCUS: Efficient Keyframe Selection for Long Video Understanding
Zirui Zhu, Hailun Xu, Yang Luo +4
Multimodal large language models (MLLMs) represent images and video frames as visual tokens. Scaling from single images to hour-long videos, however, inflates the token budget far…
Info-Coevolution: An Efficient Framework for Data Model Coevolution
Ziheng Qin, Hailun Xu, Wei Chee Yew +6
Machine learning relies heavily on data, yet the continuous growth of real-world data poses challenges for efficient dataset construction and training. A fundamental yet unsolved q…