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The result for ActivityNet #25

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@weiyuan-c

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@weiyuan-c

Hi,

Thank you for sharing your impressive work! Equipping LLMs with temporal understanding is indeed a challenging task. I have a question regarding the ActivityNet results:

Are the scores you reported directly inferred using the checkpoints provided in your GitHub repository? If so, can we reproduce the results by simply modifying the configurations and files mentioned in eval.sh (mainly adjusting folder paths, file names, and variables in eval_configs/videollama-slot-96-interpolation.yaml)?

Additionally, I noticed that the eval.sh script mentions a post_checked argument. However, the prompt file only contains prompts for each task without any reference to post_checked. Could you clarify if post_checked is required? If so, how should it be configured or included? Any advice on aligning it with the prompts would be greatly appreciated.

Looking forward to your guidance, and thank you for your time!

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