{
 "id": "cyberagent/camera",
 "owner": "cyberagent",
 "name": "camera",
 "downloads": 834,
 "likes": 7,
 "last_modified": "2024-09-02T06:29:40.000Z",
 "stated_licence": "cc-by-nc-sa-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
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 "sources": [],
 "gated": false,
 "tasks": [
  "text2text-generation",
  "image-to-text"
 ],
 "citation": "@inproceedings{mita-etal-2024-striking,\n    title = \"Striking Gold in Advertising: Standardization and Exploration of Ad Text Generation\",\n    author = \"Mita, Masato  and\n      Murakami, Soichiro  and\n      Kato, Akihiko  and\n      Zhang, Peinan\",\n    editor = \"Ku, Lun-Wei  and\n      Martins, Andre  and\n      Srikumar, Vivek\",\n    booktitle = \"Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)\",\n    month = aug,\n    year = \"2024\",\n    address = \"Bangkok, Thailand and virtual meeting\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2024.acl-long.54\",\n    pages = \"955--972\",\n    abstract = \"In response to the limitations of manual ad creation, significant research has been conducted in the field of automatic ad text generation (ATG). However, the lack of comprehensive benchmarks and well-defined problem sets has made comparing different methods challenging. To tackle these challenges, we standardize the task of ATG and propose a first benchmark dataset, CAMERA, carefully designed and enabling the utilization of multi-modal information and facilitating industry-wise evaluations. Our extensive experiments with a variety of nine baselines, from classical methods to state-of-the-art models including large language models (LLMs), show the current state and the remaining challenges. We also explore how existing metrics in ATG and an LLM-based evaluator align with human evalu",
 "signal": "restrictive",
 "reason": "The declared licence (cc-by-nc-sa-4.0) is classified as having use restrictions.",
 "revision": "2d1c23e6f3e19b9d67816bb54747770b23235779",
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}