Hallucination
Also known as: Confabulation
When a model confidently makes up something that isn't true.
When a language model generates plausible-sounding but factually incorrect information. RAG, grounding, and constrained decoding are common mitigation strategies.
In practice
The headline failure mode for any production LLM app. Be ready to defend a mitigation stack (grounding, citation, eval, abstention) for your specific use case.
How it compares
Hallucination is the failure; RAG is one of the most common mitigations for it.
Comparisons that include Hallucination
Related topics
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Related terms
Retrieval-Augmented Generation (RAG)
Fetch relevant docs at inference time and stuff them into the prompt so the model can answer from real data.
Chunking
Cutting documents into retrievable pieces before embedding them.
Context Window
The max number of tokens a model can attend to at once.
LLM Evaluation
Measuring whether an LLM does what you want, beyond "looks fine to me".
AI System Design
End-to-end design of production LLM systems: ingestion, retrieval, serving, eval, monitoring.
Perplexity
Exp(average cross-entropy) on held-out text; lower means the model is less surprised by real data.