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Published 20 hours ago • verified publisher icon gokulkarthik
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Hate-CLIPper: Multimodal Hateful Meme Classification with Explicit Cross-modal Interaction of CLIP features - Accepted at EMNLP 2022 Workshop

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detailed versions of the dependencies

Hello!Can you provide detailed versions of the dependencies listed in the requirements.txt file?

PotatoDog1669 avatar PotatoDog1669

I have a question about your code, which is the Preparation section in file 'add_image_captions.ipynb' and where is the 'utils.eval_utils' in line 'from utils.eval_utils import eval_step' .

Hello, I have carefully studied your Hate CLIPPer paper and code. I have a question about your code, which is the Preparation section in file 'add_image_captions.ipynb' and where is the...

WuFannnn avatar WuFannnn

Regarding the Dataset

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Is the dataset used in your code preprocessed? I noticed that the structure of your dataset differs from the Hateful Memes dataset I found on Kaggle. Thank you for your...

YOUKAINOYAMA avatar YOUKAINOYAMA

Pretained model

I want to know that if there has your pretained model?

15114842111 avatar 15114842111

Dataset?

Hello @gokulkarthik , your work is really interesting Could you feel free to share the HMC, and Propaganda Dataset? Because I cannot find it on the internet. Your help would...

ngthanhtin avatar ngthanhtin

torchmetrics

Hi, thank you for sharing your code. I am wondering if there is a bug in the evaluation of the Propaganda Meme dataset. In the evaluation procedure, torchmetrics.F1 receives preds...

yutaro-s avatar yutaro-s

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verified publisher icon gokulkarthik

Metadata

Hate-CLIPper: Multimodal Hateful Meme Classification with Explicit Cross-modal Interaction of CLIP features - Accepted at EMNLP 2022 Workshop

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