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cs.CV2026
ViLL-E: Video LLM Embeddings for Retrieval
Rohit Gupta, Jayakrishnan Unnikrishnan, Fan Fei +3
Video Large Language Models (VideoLLMs) excel at video understanding tasks where outputs are textual, such as Video Question Answering and Video Captioning. However, they underperf…
cs.CV2024
VidLA: Video-Language Alignment at Scale
Mamshad Nayeem Rizve, Fan Fei, Jayakrishnan Unnikrishnan +5
In this paper, we propose VidLA, an approach for video-language alignment at scale. There are two major limitations of previous video-language alignment approaches. First, they do…