mlsanityData to 7 Oct 2026

Regulatory gray areas of LLM Terms

arXiv 2601.08415 ↗First posted 13 Jan 2026cs.CY cs.AIcited by 2

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Abstract (arXiv)

Large Language Models (LLMs) are increasingly integrated into academic research pipelines; however, the Terms of Service governing their use remain under-examined. We present a comparative analysis of the Terms of Service of five major LLM providers (Anthropic, DeepSeek, Google, OpenAI, and xAI) collected in November 2025. Our analysis reveals substantial variation in the stringency and specificity of usage restrictions for general users and researchers. We identify specific complexities for researchers in security research, computational social sciences, and psychological studies. We identify `regulatory gray areas' where Terms of Service create uncertainty for legitimate use. We contribute a publicly available resource comparing terms across platforms (OSF) and discuss implications for general users and researchers navigating this evolving landscape.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 9 of its 37 references that are in the map. First posted on arXiv 13 Jan 2026.

Builds on

9 of 37 references.

References · 9

  1. 2023Sentiment Analysis in the Era of Large Language Models: A Reality Checkcited by 262
  2. 2025Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providerscited by 67
  3. 2020Privacy Policies over Time: Curation and Analysis of a Million-Document Datasetcited by 28
  4. 2024Scaling Trends for Data Poisoning in LLMscited by 26
  5. 2024Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superpositioncited by 13
  6. 2024Large Models of What? Mistaking Engineering Achievements for Human Linguistic Agencycited by 9
  7. 2025The Accountability Paradox: How Platform API Restrictions Undermine AI Transparency Mandatescited by 7
  8. 2025Between Help and Harm: An Evaluation of Mental Health Crisis Handling by LLMscited by 6
  9. 2025ChatGPT or A Silent Everywhere Helper: A Survey of Large Language Modelscited by 1

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Citing papers per year: 2026: 2.

2 papers.