A Concise Review of Hallucinations in LLMs and their Mitigation
It addresses the challenge of hallucinations in LLMs for the NLP community, but it is incremental as it only reviews existing information without new contributions.
The paper reviews the problem of hallucinations in language models and summarizes existing knowledge on their types, origins, and mitigation strategies, serving as a concise resource for general understanding.
Traditional language models face a challenge from hallucinations. Their very presence casts a large, dangerous shadow over the promising realm of natural language processing. It becomes crucial to understand the various kinds of hallucinations that occur nowadays, their origins, and ways of reducing them. This document provides a concise and straightforward summary of that. It serves as a one-stop resource for a general understanding of hallucinations and how to mitigate them.