Terminators: Terms of Service Parsing and Auditing Agents

May 16, 2025 Β· Declared Dead Β· πŸ› Companion Publication of the 17th ACM Web Science Conference 2025

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Authors Maruf Ahmed Mridul, Inwon Kang, Oshani Seneviratne arXiv ID 2505.11672 Category cs.IR: Information Retrieval Citations 1 Venue Companion Publication of the 17th ACM Web Science Conference 2025 Last Checked 4 months ago
Abstract
Terms of Service (ToS) documents are often lengthy and written in complex legal language, making them difficult for users to read and understand. To address this challenge, we propose Terminators, a modular agentic framework that leverages large language models (LLMs) to parse and audit ToS documents. Rather than treating ToS understanding as a black-box summarization problem, Terminators breaks the task down to three interpretable steps: term extraction, verification, and accountability planning. We demonstrate the effectiveness of our method on the OpenAI ToS using GPT-4o, highlighting strategies to minimize hallucinations and maximize auditability. Our results suggest that structured, agent-based LLM workflows can enhance both the usability and enforceability of complex legal documents. By translating opaque terms into actionable, verifiable components, Terminators promotes ethical use of web content by enabling greater transparency, empowering users to understand their digital rights, and supporting automated policy audits for regulatory or civic oversight.
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