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gvclab/awesome-reasoning-via-vdm
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Help me build a tool that analyzes a how-to video and explains each step. Using the awesome-reasoning-via-vdm reading list as a starting point, what papers or projects should I look at first, and how do their approaches differ?
I want to evaluate whether an AI model can follow a game of chess from video footage alone. The awesome-reasoning-via-vdm list points to benchmarks for this, help me design an evaluation plan based on those benchmarks.
From the awesome-reasoning-vdm collection, summarize the key methods that teach video models to reason by generating intermediate visual frames as part of their thinking process. Which approach seems most promising for a prototype?
Help me organize the awesome-reasoning-via-vdm reading list into a learning curriculum. What order should I read these papers in to build up my understanding of video reasoning in AI, starting from foundational concepts?
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