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cs.CL2024
IPS: In-Prompt Process Supervision for Short Video Content Moderation
Mingchao Liu, Yu Sun, Ruixiao Sun +5
Multimodal large language models (MLLMs) are effective at capturing the semantics of short video content; however, they often fail to attend to the policy-specific details required…
cs.IR2024
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…
cs.CV2024
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…