Agree To Disagree
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Abstract (arXiv)
How frequently do individuals thoroughly review terms and conditions before proceeding to register for a service, install software, or access a website? The majority of internet users do not engage in this practice. This trend is not surprising, given that terms and conditions typically consist of lengthy documents replete with intricate legal terminology and convoluted sentences. In this paper, we introduce a Machine Learning-powered approach designed to automatically parse and summarize critical information in a user-friendly manner. This technology focuses on distilling the pertinent details that users should contemplate before committing to an agreement.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 10 references that are in the map. First posted on arXiv 24 Sep 2023.
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