3 papers
cs.CV2026
When Rules Fall Short: Agent-Driven Discovery of Emerging Content Issues in Short Video Platforms
Chenghui Yu, Hongwei Wang, Junwen Chen +5
Trends on short-video platforms evolve at a rapid pace, with new content issues emerging every day that fall outside the coverage of existing annotation policies. However, traditio…
cs.CV2025
COEF-VQ: Cost-Efficient Video Quality Understanding through a Cascaded Multimodal LLM Framework
Xin Dong, Sen Jia, Ming Rui Wang +4
Recently, with the emergence of recent Multimodal Large Language Model (MLLM) technology, it has become possible to exploit its video understanding capability on different classifi…
cs.IR2025
USM: Unbiased Survey Modeling for Limiting Negative User Experiences in Recommendation Systems
Chenghui Yu, Peiyi Li, Haoze Wu +3
Reducing negative user experiences is essential for the success of recommendation platforms. Exposing users to inappropriate content could not only adversely affect users' psycholo…