Sources & Further Reading
iSources checked: September 2026
The content of this module was researched in May 2026; all source links were checked for availability in September 2026 and updated where needed. Since AI capabilities and tools evolve rapidly, some details may have changed since then.
Sources
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Ji, Z. et al. (2023). Survey of Hallucination in Natural Language Generation. ACM Computing Surveys. https://dl.acm.org/doi/10.1145/3571730
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Huang, L. et al. (2023). A Survey on Hallucination in Large Language Models. arXiv:2311.05232. https://arxiv.org/abs/2311.05232
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Stanford HAI (2025). AI Index Report 2025 -- AI Reliability and Trustworthiness. https://aiindex.stanford.edu/report/
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Ahlstrom-Vij, K. (2024). Epistemic Trust and AI. Cambridge University Press. Analysis of handling AI-generated information.
Further Reading
Research Methods
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Google Scholar: Academic search engine for scientific publications. Indispensable for verifying studies and research results. https://scholar.google.com
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Semantic Scholar: AI-powered academic search engine with automatic summarization and citation analysis. https://www.semanticscholar.org
Fact-Checking
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Snopes: One of the oldest and best-known fact-checking websites. https://www.snopes.com
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CORRECTIV: German non-profit research center focusing on fact-checking. https://correctiv.org
Knowledge Management
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Luhmann, N. -- Zettelkasten Method: The principle of networked notes, now implemented through digital tools like Obsidian and Logseq. https://niklas-luhmann-archiv.de/
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Tiago Forte -- Building a Second Brain: Popular method for personal knowledge organization. https://www.buildingasecondbrain.com
Background
- Anthropic -- Claude Model Card: Documentation on Claude's capabilities and limitations, including information on hallucination rates. https://platform.claude.com/docs/en/models/overview