{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,3]],"date-time":"2022-04-03T06:28:48Z","timestamp":1648967328361},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T00:00:00Z","timestamp":1638403200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,2]]},"abstract":"<jats:p>In this paper, we introduce BART2S a novel framework based on BART pretrained models to generate terms of service in high quality. The framework contains two parts: a generator finetuned with multiple tasks and a discriminator fine-tuned to distinguish the fair and unfair terms. Besides the novelty in design and the implementation contributions, the proposed framework can support drafting terms of service, a growing need in the digital age. Our proposed approach allows the system to reach a balance between automation and the will expression of the service provider. Through experiments, we demonstrate the effectiveness of the method and discuss potential future directions.<\/jats:p>","DOI":"10.3233\/faia210325","type":"book-chapter","created":{"date-parts":[[2021,12,7]],"date-time":"2021-12-07T09:13:09Z","timestamp":1638868389000},"source":"Crossref","is-referenced-by-count":0,"title":["Few-Shot Tuning Framework for Automated Terms of Service Generation"],"prefix":"10.3233","author":[{"given":"Ha Thanh","family":"Nguyen","sequence":"first","affiliation":[{"name":"Japan Advanced Institute of Science and Technology"}]},{"given":"Kiyoaki","family":"Shirai","sequence":"additional","affiliation":[{"name":"Japan Advanced Institute of Science and Technology"}]},{"given":"Le Minh","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Japan Advanced Institute of Science and Technology"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Legal Knowledge and Information Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA210325","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,7]],"date-time":"2021-12-07T09:46:59Z","timestamp":1638870419000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA210325"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,2]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia210325","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,2]]}}}