How Language Model Hallucinations Can Snowball · HackerPapers discussions

How Language Model Hallucinations Can Snowball — mentioned by ACCount37

Sun, 28 Dec 2025 16:30:54 GMT

We have this write-up on the "soul" and how it was discovered and extracted, straight from the source: https://www.lesswrong.com/posts/vpNG99GhbBoLov9og/claude-4-5... There are many pragmatic reasons to take this "soul data" approach, but we don't know exactly what Anthropic's reasoning was in this case. We just know enough to say that it's likely to improve LLM behavior overall. Now, on consistency drive and compounding errors in LLM behavior: sadly, no really good overview papers that come to mind? The topic was investigated the most in the early days of chatbot LLMs, in part because some…

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How Language Model Hallucinations Can Snowball — mentioned by jpcompartir

Tue, 09 Sep 2025 14:10:59 GMT

Assuming you've read OpenAI's paper released this week? https://cdn.openai.com/pdf/d04913be-3f6f-4d2b-b283-ff432ef4a... They attribute these 'compression artefacts' to pre-training, they also reference the original snowballing paper: How Language Model Hallucinations Can Snowball: https://arxiv.org/pdf/2305.13534 They further state that reasoning is no panacea. W hilst you did say: "the models mitigate more and more" You were replying to my comment which said: "'Bad' generations early in the output sequence are somewhat mitigatable by injecting self-reflection tokens like 'wait', or with more…

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How Language Model Hallucinations Can Snowball — mentioned by intended

Mon, 26 Feb 2024 05:46:57 GMT

https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=llm+... https://www.medpagetoday.com/ophthalmology/generalophthalmol.... - Survey of Hallucination in Natural Language Generation](https://arxiv.org/abs/2202.03629) (Ji et al., 2022) - [How Language Model Hallucinations Can Snowball](https://arxiv.org/abs/2305.13534) (Zhang et al., 2023) - [A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity](https://arxiv.org/abs/2302.04023) (Bang et al., 2023) - [Contrastive Learning Reduces Hallucination in…

Paper and discussion history. A mention is not an endorsement.

How Language Model Hallucinations Can Snowball — HN submission

Mon, 29 May 2023 06:20:14 GMT

How Language Model Hallucinations Can Snowball

2 points; 1 discussion reply on HN. Paper and source history. A submission is not an endorsement.

How Language Model Hallucinations Can Snowball — mentioned by lambdaviking

Fri, 26 May 2023 22:02:02 GMT

> How do the results of your work inform these predictions that stack-more-layers token-prediction scaling will keep unlocking new abilities? The short answer is that scaling up alone probably won't fix these shortcomings. Better decoding strategies like CoT may help, but the issue we're identifying is a limitation of any transformer (no matter the size) arising from its parallelism (the property that enables scaling to large model size/data volume). As some evidence of this, we were able to use these results to find simple problems that ChatGPT and GPT4 get chance performance on. Moreover…

Paper and discussion history. A mention is not an endorsement.