AI Glossary
Hallucination
Understanding AI Terminology
When an AI model generates false or made-up information that sounds plausible.
What It Means
Hallucination refers to AI-generated content that is factually incorrect, fabricated, or inconsistent with reality, despite sounding confident and plausible. LLMs can hallucinate because they generate text based on patterns rather than verified knowledge. Common hallucinations include made-up citations, incorrect statistics, and fictional events presented as fact.
Examples
- Citing academic papers that don't exist
- Generating plausible-sounding but incorrect code
- Making up historical dates or events
How This Applies to ARKA-AI
ARKA-AI encourages verification of AI outputs and offers research tools that help fact-check information.
Frequently Asked Questions
Common questions about Hallucination
Ask the AI to cite sources, verify important facts independently, use RAG systems with trusted data, and be skeptical of specific claims like dates, numbers, and citations.
Hallucination rates vary by model and task. Generally, more capable models and those with retrieval augmentation hallucinate less, but no model is immune.
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