iaadlab/FutureGen

📚 ACL & NeurIPS Future Work Dataset

This dataset contains curated "Future Work" sections from ACL and NeurIPS research papers. It is designed to support tasks like scientific document understanding, future work generation, citation intent analysis, and summarization of research directions.

📦 Dataset Details

🔍 Dataset Description

This dataset includes:

• ACL_2012.csv to ACL_2024.csv: Tabular data where each row is a paper and each column represents a paper section (e.g., Abstract, Introduction, Future Work).
• NeurIPS_2021.csv, NeurIPS_2022.csv: Similar format as ACL .csv files.
• ACL_2023.json, ACL_2024.json: Each file contains paper-wise parsed output including section headers and content. "Future Work" sections are extracted and added if found.

Each record is either a paper (in .csv) or a structured section-by-section breakdown of a paper (in .json). If a paper does not contain a "Future Work" section, it has been excluded from the .json.

• Languages: English
• Total Papers (after filtering): Varies by year (see Statistics section on HF for breakdown)
• Data format: .csv, .json

✍️ Curated by

Ibrahim Al Azher, Northern Illinois University, DATALab

📑 Dataset Structure

For .csv Files:

Each file contains:

• Columns: 'title', 'abstract', 'introduction', 'related work', ..., 'future work'
• Rows: One paper per row
• Year-specific files (ACL_2012.csv to ACL_2024.csv)

For .json Files:

Each key is a paper ID (e.g., "ACL23_1.pdf") and its value includes:

{
  "abstractText": "string",
  "sections": [
    { "heading": "Introduction", "text": "..." },
    ...
    { "heading": "Future Work", "text": "..." }
  ],
  "title": "string",
  "year": "int"
}