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Large Language Models as Automated Aligners for benchmarking Vision-Language Models
In this work, we address the limitations via Auto-Bench, which delves into exploring LLMs as proficient aligners, measuring the alignment between VLMs and human intelligence and value through automatic data curation and assessment.
Video Question Answering Using CLIP-Guided Visual-Text Attention
Specifically, we first extract video features using a TimeSformer and text features using a BERT from the target application domain, and utilize CLIP to extract a pair of visual-text features from the general-knowledge domain through the domain-specific learning.
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