---
title: "Extrinsic Hallucinations in LLMs"
url: https://daily.dev/posts/extrinsic-hallucinations-in-llms-jg5b5dbyw
source_url: https://lilianweng.github.io/posts/2024-07-07-hallucination/
type: article
source: "Lil’Log"
published: 2024-07-08T06:37:58.924Z
updated: 2024-10-05T17:22:24.538Z
tags: ["ai", "machine-learning", "nlp", "llm"]
reading_time: 27
upvotes: 13
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Extrinsic Hallucinations in LLMs

**[Lil’Log](https://daily.dev/sources/lilianweng)** · 27 min read · 13 upvotes · 0 comments

## Summary

Hallucination in large language models (LLMs) refers to generating unfaithful, fabricated, or nonsensical content not grounded in provided context or world knowledge. The focus is on extrinsic hallucination, emphasizing the need for LLMs to produce factual content and acknowledge when they lack knowledge. Causes of hallucination include issues during pre-training and fine-tuning stages. Various methods, like retrieval-augmented generation (RAG), special sampling methods, and fine-tuning for factuality, are explored to minimize hallucinations. Evaluation benchmarks and different detection approaches are also discussed.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://lilianweng.github.io/posts/2024-07-07-hallucination/>

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---

Tags: [#ai](https://daily.dev/tags/ai), [#machine-learning](https://daily.dev/tags/machine-learning), [#nlp](https://daily.dev/tags/nlp), [#llm](https://daily.dev/tags/llm)

[View this post on daily.dev](https://daily.dev/posts/extrinsic-hallucinations-in-llms-jg5b5dbyw)