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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2303.08896/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2303.08896/feed.xml" rel="self" type="application/rss+xml" /><item><title>SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models — mentioned by gmerc</title><link>https://news.ycombinator.com/item?id=40772649</link><guid isPermaLink="false">urn:hackerpapers:mention:2303.08896:40772649</guid><pubDate>Mon, 24 Jun 2024 04:22:33 GMT</pubDate><description>&lt;p&gt;This seems to do the same as this paper from last year but getting more press. https://arxiv.org/abs/2303.08896&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2303.08896/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models — mentioned by gmerc</title><link>https://news.ycombinator.com/item?id=40544096</link><guid isPermaLink="false">urn:hackerpapers:mention:2303.08896:40544096</guid><pubDate>Sat, 01 Jun 2024 09:07:45 GMT</pubDate><description>&lt;p&gt;Prediction implies inaccuracy https://arxiv.org/abs/2303.08896&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2303.08896/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models — mentioned by intended</title><link>https://news.ycombinator.com/item?id=39508017</link><guid isPermaLink="false">urn:hackerpapers:mention:2303.08896:39508017</guid><pubDate>Mon, 26 Feb 2024 05:46:57 GMT</pubDate><description>&lt;p&gt;https://scholar.google.com/scholar?hl=en&amp;amp;as_sdt=0%2C5&amp;amp;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…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2303.08896/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models — mentioned by famouswaffles</title><link>https://news.ycombinator.com/item?id=37670163</link><guid isPermaLink="false">urn:hackerpapers:mention:2303.08896:37670163</guid><pubDate>Wed, 27 Sep 2023 04:31:06 GMT</pubDate><description>&lt;p&gt;https://arxiv.org/abs/2305.18248 &amp;quot;In particular, we find that LMs often hallucinate differing authors of hallucinated references when queried in independent sessions, while consistently identify authors of real references. This suggests that the hallucination may be more a generation issue than inherent to current training techniques or representation.&amp;quot; https://arxiv.org/abs/2303.08896 &amp;quot;SelfCheckGPT leverages the simple idea that if a LLM has knowledge of a given concept, sampled responses are likely to be similar and contain consistent facts. However, for hallucinated facts, stochastically…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2303.08896/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models — mentioned by famouswaffles</title><link>https://news.ycombinator.com/item?id=37670158</link><guid isPermaLink="false">urn:hackerpapers:mention:2303.08896:37670158</guid><pubDate>Wed, 27 Sep 2023 04:30:29 GMT</pubDate><description>&lt;p&gt;automatically comparing drafts for every single query would be expensive. and that wouldn&amp;#x27;t eliminate hallucinations just tell you if large details have likely been hallucinated. But it&amp;#x27;s a method some research has used. https://arxiv.org/abs/2303.08896&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2303.08896/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
