{
 "id": "google/air_dialogue",
 "owner": "google",
 "name": "air_dialogue",
 "downloads": 330,
 "likes": 22,
 "last_modified": "2024-03-07T15:22:15.000Z",
 "stated_licence": "cc-by-nc-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "text-generation",
  "fill-mask"
 ],
 "citation": "@inproceedings{wei-etal-2018-airdialogue,\n    title = \"{A}ir{D}ialogue: An Environment for Goal-Oriented Dialogue Research\",\n    author = \"Wei, Wei  and\n      Le, Quoc  and\n      Dai, Andrew  and\n      Li, Jia\",\n    editor = \"Riloff, Ellen  and\n      Chiang, David  and\n      Hockenmaier, Julia  and\n      Tsujii, Jun{'}ichi\",\n    booktitle = \"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing\",\n    month = oct # \"-\" # nov,\n    year = \"2018\",\n    address = \"Brussels, Belgium\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/D18-1419\",\n    doi = \"10.18653/v1/D18-1419\",\n    pages = \"3844--3854\",\n    abstract = \"Recent progress in dialogue generation has inspired a number of studies on dialogue systems that are capable of accomplishing tasks through natural language interactions. A promising direction among these studies is the use of reinforcement learning techniques, such as self-play, for training dialogue agents. However, current datasets are limited in size, and the environment for training agents and evaluating progress is relatively unsophisticated. We present AirDialogue, a large dataset that contains 301,427 goal-oriented conversations. To collect this dataset, we create a context-generator which provides travel and flight restrictions. We then ask human annotators to play the role of a customer or an agent and interact with the goal of successfully booking a trip given the restrictions. ",
 "signal": "restrictive",
 "reason": "The declared licence (cc-by-nc-4.0) is classified as having use restrictions.",
 "revision": "dbdbe7bcef8d344bc3c68a05600f3d95917d6898",
 "stated_evidence": "https://huggingface.co/datasets/google/air_dialogue/blob/dbdbe7bcef8d344bc3c68a05600f3d95917d6898/README.md",
 "file_evidence": "https://huggingface.co/datasets/google/air_dialogue/tree/dbdbe7bcef8d344bc3c68a05600f3d95917d6898",
 "card_nc": false
}