Interpretation Gaps in LLM-Assisted Comprehension of Privacy Documents
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Abstract (arXiv)
This article explores the gaps that can manifest when using a large language model (LLM) to obtain simplified interpretations of data practices from a complex privacy policy. We exemplify these gaps to showcase issues in accuracy, completeness, clarity and representation, while advocating for continued research to realize an LLM's true potential in revolutionizing privacy management through personal assistants and automated compliance checking.
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References · 12
- 2017Attention Is All You Needcited by 60,361
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
- 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,455
- 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,276
- 2023A Comprehensive Overview of Large Language Modelscited by 648
- 2024The Butterfly Effect of Altering Prompts: How Small Changes and Jailbreaks Affect Large Language Model Performancecited by 100
- 2024GoldCoin: Grounding Large Language Models in Privacy Laws via Contextual Integrity Theorycited by 37
- 2023On Context Utilization in Summarization with Large Language Modelscited by 30
- 2024Large Language Models: A New Approach for Privacy Policy Analysis at Scalecited by 14
- 2024Rethinking Legal Compliance Automation: Opportunities with Large Language Modelscited by 6
- 2024LegiLM: A Fine-Tuned Legal Language Model for Data Compliancecited by 6
- 2024Privacy Policy Analysis through Prompt Engineering for LLMscited by 6
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