Papers by Vaishnavi Himakunthala

1 papers
Let’s Think Frame by Frame with VIP: A Video Infilling and Prediction Dataset for Evaluating Video Chain-of-Thought (2023.emnlp-main)

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Challenge: Existing studies show vision-language systems can reason about images using natural language, but their capacity for video reasoning remains underexplored.
Approach: They propose to frame video reasoning as the sequential understanding of a small number of keyframes, thereby leveraging the power and robustness of vision-language systems' capacity to reason about images using natural language.
Outcome: The proposed models can generate multiple intermediate keyframes and predict future keyframe, and they perform poorly on GPT-4, GPT-3, and VICUNA.

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