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I think it qualifies as a hallucination. What's your definition? I'm a researcher too and as far as I'm aware the definition has always been pretty broad and ap

I think it qualifies as a hallucination. What's your definition? I'm a researcher too and as far as I'm aware the definition has always been pretty broad and applied to many forms of mistakes. (It was always muddy but definitely got more muddy when adopted by NLP) It's hard to know why it made the error but isn't it caused by inaccurate "world" modeling? ("World" being English language) Is it not making some hallucination about the English language while interpreting the prompt or document? I'm having a hard time trying to think of a context where "they" would even be first person. I can't find any search results though Google's AI says it can. It provided two links, the first being a Quora result saying people don't do this but framed it as it's not impossible, just unheard of. Second result just talks about singular you. Both of these I'd consider hallucinations too as the answer isn't supported by the links.

simonw 1y ago
My personal definition of hallucination (which I thought was widespread) is when a model states a fact about the world that is entirely made up - "the James Webb telescope took the first photograph of an exoplanet" for example. I just got pointed to this new paper: https://arxiv.org/abs/2508.01781 https://arxiv.org/abs/2508.01781 - "A comprehensive taxonomy of hallucinations in Large Language Models" - which has a definition in the introduction which matches my mental model: "This phenomenon describes the generation of content that, while often plausible and coherent, is factually incorrect, inconsistent, or entirely fabricated." The paper then follows up with a formal definition; "inconsistency between a computable LLM, denoted as h, and a computable ground truth function, f"
- godelski 1y ago
  Google (the company, not the search engine) says[0] | AI hallucinations are incorrect or misleading results that AI models generate. It goes on further to give examples and I think this is clearly a false positive result. > this new paper I think the error would have no problem fitting under "Contextual inconsistencies" (4.2), "Instruction inconsistencies/deviation" (4.3), or "Logical inconsistencies" (4.4). I think it supports a pretty broad definition. I think it also fits under other categories defined in section 4. > then follows up with a formal definition Is this not a computable ground truth? | an LLM h is considered to be ”hallucinating” with respect to a ground truth function f if, across all training stages i (meaning, after being trained on any finite number of samples), there exists at least one input string s for which the LLM’s output h[i](s) does not match the correct output f (s)[100]. This condition is formally expressed as ∀i ∈ N, ∃s ∈ S such that h[i](s)̸ = f (s). I think yes, this is an example of such an "i" and I would go so far as reclaiming that this is a pretty broad definition. Just saying that it is considered hallucinating if it makes something up that it was trained on (as opposed to something it wasn't trained on). I'm pretty confident the LLMs ingested a lot of English grammar books so I think it is fair to say that this was in the training. [0] https://cloud.google.com/discover/what-are-ai-hallucinations https://cloud.google.com/discover/what-are-ai-hallucinations

simonw 1y ago

My personal definition of hallucination (which I thought was widespread) is when a model states a fact about the world that is entirely made up - "the James Webb telescope took the first photograph of an exoplanet" for example. I just got pointed to this new paper: https://arxiv.org/abs/2508.01781 https://arxiv.org/abs/2508.01781 - "A comprehensive taxonomy of hallucinations in Large Language Models" - which has a definition in the introduction which matches my mental model: "This phenomenon describes the generation of content that, while often plausible and coherent, is factually incorrect, inconsistent, or entirely fabricated." The paper then follows up with a formal definition; "inconsistency between a computable LLM, denoted as h, and a computable ground truth function, f"

godelski 1y ago
Google (the company, not the search engine) says[0] | AI hallucinations are incorrect or misleading results that AI models generate. It goes on further to give examples and I think this is clearly a false positive result. > this new paper I think the error would have no problem fitting under "Contextual inconsistencies" (4.2), "Instruction inconsistencies/deviation" (4.3), or "Logical inconsistencies" (4.4). I think it supports a pretty broad definition. I think it also fits under other categories defined in section 4. > then follows up with a formal definition Is this not a computable ground truth? | an LLM h is considered to be ”hallucinating” with respect to a ground truth function f if, across all training stages i (meaning, after being trained on any finite number of samples), there exists at least one input string s for which the LLM’s output h[i](s) does not match the correct output f (s)[100]. This condition is formally expressed as ∀i ∈ N, ∃s ∈ S such that h[i](s)̸ = f (s). I think yes, this is an example of such an "i" and I would go so far as reclaiming that this is a pretty broad definition. Just saying that it is considered hallucinating if it makes something up that it was trained on (as opposed to something it wasn't trained on). I'm pretty confident the LLMs ingested a lot of English grammar books so I think it is fair to say that this was in the training. [0] https://cloud.google.com/discover/what-are-ai-hallucinations https://cloud.google.com/discover/what-are-ai-hallucinations