There's a labeled dataset for this! https://t.co/ieOdjn4MiU. Aside: if you know your end-task ahead of time, a domain-specific model (e.g. BERT trained to classify fair/unfair ToS) is almost always going to be much more efficient to train and deploy than a
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@LawMcGill Parts of what I will cover you can read in the papers written by the great @Claudette_EUI team, including: "CLAUDETTE: an automated detector of potentially unfair clauses in online terms of service" https://t.co/OXsz70mOxW /1
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RT @shunk031: 英語の規約中不公平文検出に関する先行研究はこれか / [1805.01217] CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Ser…
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英語の規約中不公平文検出に関する先行研究はこれか / [1805.01217] CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service https://t.co/NUfbib5ile