Extrinsic Hallucinations in LLMs

Linking pages

[AINews] Test-Time Training, MobileLLM, Lilian Weng on Hallucination (Plus: Turbopuffer) • Buttondown https://buttondown.email/ainews/archive/ainews-to-be-named-3686/ 0 comments

Linked pages

[2403.18802] Long-form factuality in large language models https://arxiv.org/abs/2403.18802 76 comments
Prompt Engineering | Lil'Log https://lilianweng.github.io/posts/2023-03-15-prompt-engineering/ 59 comments
[2309.03883] DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models https://arxiv.org/abs/2309.03883 43 comments
[2405.05904] Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations? https://arxiv.org/abs/2405.05904 17 comments
[2109.07958] TruthfulQA: Measuring How Models Mimic Human Falsehoods https://arxiv.org/abs/2109.07958 7 comments
[2207.05221] Language Models (Mostly) Know What They Know https://arxiv.org/abs/2207.05221 6 comments
[2112.09332] WebGPT: Browser-assisted question-answering with human feedback https://arxiv.org/abs/2112.09332 3 comments
[2306.03341] Inference-Time Intervention: Eliciting Truthful Answers from a Language Model https://arxiv.org/abs/2306.03341 1 comment
How to Build an Open-Domain Question Answering System? | Lil'Log https://lilianweng.github.io/posts/2020-10-29-odqa/ 0 comments
[2305.18248] Do Language Models Know When They're Hallucinating References? https://arxiv.org/abs/2305.18248 0 comments
[2309.11495] Chain-of-Verification Reduces Hallucination in Large Language Models https://arxiv.org/abs/2309.11495 0 comments
Controllable Neural Text Generation | Lil'Log https://lilianweng.github.io/posts/2021-01-02-controllable-text-generation/ 0 comments
[2305.18153] Do Large Language Models Know What They Don't Know? https://arxiv.org/abs/2305.18153 0 comments
Diffusion Models for Video Generation | Lil'Log https://lilianweng.github.io/posts/2024-04-12-diffusion-video/ 0 comments
[2405.01525] FLAME: Factuality-Aware Alignment for Large Language Models https://arxiv.org/abs/2405.01525 0 comments