{
  "fetched_at": "2026-10-19T10:38:42Z",
  "source_url": "https://www.kaggle.com/competitions/dl-hack-track-2-nlp/data",
  "pages": [
    {
      "name": "data-description",
      "content": "# Dataset\n\nFor nearly 30 years, [Arxiv](https://arxiv.org) has served the public and research communities by providing open access to scholarly articles, from the vast branches of physics to the many subdisciplines of computer science to everything in between, including math, statistics, electrical engineering, quantitative biology, and economics. From this collection, papers are selected from the categories: [cs.CV, cs.AI, cs.LG, cs.CL, cs.NE, stat.ML] and their corresponding titles, abstracts are extracted as metadata to build a large corpus containing 1,47,381 entries. The test set contains 1,000 samples for evaluation.\n\n# Submission\nThe final submission file must contain 33 columns - **\"id\"**: paper id and columns ranging from **\"f_0-f_31\"**: each index of the embedding vector. Sample submission file can be found in the provided dataset.\n\nFor more information please visit: https://analytics-club-iitm.github.io/DL-Hack-20-21/track2",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Description",
      "content": "# Description\n\nRecent improvements in Language models have led to substantial progress on various NLP tasks like text classification, question-answering, information-retrieval, etc. Text Generation (or) the task of generating text with the goal of appearing indistinguishable to human-written text is one such task that has captured the attention of researchers ([GPT-3](https://github.com/elyase/awesome-gpt3)).\n\nIn this challenge, you will be required to generate abstracts for research papers from their titles. Unlike text summarization, this is a more demanding task as the model needs to predict an entire paragraph from just 5-6 words present in the title, capture cues regarding the progress of research in a specific topic, and most importantly ensure novelty. \n\nFor more information please visit: https://analytics-club-iitm.github.io/DL-Hack-20-21/track2",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
  ]
}