Analyzing Hallucinations in LLMs: A Mathematical Approach to Mitigation

This ArXiv article suggests a rigorous, mathematical approach to understanding and mitigating the problem of hallucinations in Large Language Models (LLMs). The focus on uncertainty quantification and advanced decoding methods offers a promising avenue for improving the reliability of LLM outputs.

• •Applies mathematical analysis to understand LLM hallucinations.
• •Investigates uncertainty quantification as a means of reducing hallucinations.
• •Proposes advanced decoding strategies to improve output reliability.