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---
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language:
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- en
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license: cc-by-nc-nd-4.0
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configs: # Optional. This can be used to pass additional parameters to the dataset loader, such as `data_files`, `data_dir`, and any builder-specific parameters
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- config_name: default # Name of the dataset subset, if applicable. Example: default
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data_files:
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- split: train # Example: train
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path: train/* # Example: data.csv
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- split: dev # Example: test
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path: dev/* # Example: holdout.csv
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- split: test # Example: test
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path: test/* # Example: holdout.csv
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dataset_info:
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features:
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- name: video_path # Example: id
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dtype: string # Example: int32
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- name: abstract # Example: text
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dtype: string # Example: string
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- name: language # Example: image
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dtype: string # Example: image
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- name: split # Example: image
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dtype: string # Example: image
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- name: conference # Example: image
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dtype: string # Example: image
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- name: year # Example: image
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dtype: string # Example: image
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config_name: default # Name of the dataset subset. Example for glue: sst2
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splits:
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- name: train # Example: train
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num_examples: 4333 # Example for SQuAD: 87599
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- name: dev # Example: train
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num_examples: 886 # Example for SQuAD: 87599
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- name: test # Example: train
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num_examples: 1432 # Example for SQuAD: 87599
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---
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# Abstract Generation with ACL talks
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This dataset is designed for the task of Multimodal Abstract Generation from scientific talks.
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It provides links to videos of academic presentations from ACL conferences, paired with their corresponding abstracts.
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The goal is to generate concise, informative summaries (abstracts) based on the content.
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Soon, we will also upload the audio files for easier usage!
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## Citation
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A dataset paper will be available soon.
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