Demo: TOSense -- What Did You Just Agree to?
Not on the map. Why?
Abstract (arXiv)
Online services often require users to agree to lengthy and obscure Terms of Service (ToS), leading to information asymmetry and legal risks. This paper proposes TOSense-a Chrome extension that allows users to ask questions about ToS in natural language and get concise answers in real time. The system combines (i) a crawler "tos-crawl" that automatically extracts ToS content, and (ii) a lightweight large language model pipeline: MiniLM for semantic retrieval and BART-encoder for answer relevance verification. To avoid expensive manual annotation, we present a novel Question Answering Evaluation Pipeline (QEP) that generates synthetic questions and verifies the correctness of answers using clustered topic matching. Experiments on five major platforms, Apple, Google, X (formerly Twitter), Microsoft, and Netflix, show the effectiveness of TOSense (with up to 44.5% accuracy) across varying number of topic clusters. During the demonstration, we will showcase TOSense in action. Attendees will be able to experience seamless extraction, interactive question answering, and instant indexing of new sites.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 7 references that are in the map. First posted on arXiv 1 Aug 2025.
Builds on
3 of 7 references.
References · 3
- 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
- 2018CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Servicecited by 73
- 2018Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learningcited by 50
Built on by
Not cited yet.