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GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2

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Re: GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2

#121

Post by an0malous »

wolttam wrote: post #113

> it is clear that actual intelligence has plateaued significantly. > Moving forward, the industry cannot continue to train bigger and bigger models since their intelligence not only plateaus but often will get worse These are wild claims - why are we concluding that bigger models and more data = more hallucination? That’s actually the opposite of what’s been happening over the last couple years. Some models may stil…

> why are we concluding that bigger models and more data = more hallucination?

That’s not what your quotes said. They said bigger models = plateau in intelligence, nothing about more data or increased hallucinations

The relevant quote for what you’re talking about would be:

> It’s been proven that when a model is trained on large volumes of highly factual and non-theoretical data, it learns to always have an answer.

So there’s two separate claims: 1) bigger models have plateauing results 2) models trained on larger amounts of factual data have a higher hallucination rate

I’m pretty sure #1 is well known, I think OpenAI’s own research on scaling laws showed diminishing returns on parameter count and training data volume years ago. I don’t know what the support for #2 is besides for the actual post contents.

Re: GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2

#122

Post by jampekka »

wongarsu wrote: post #95
stalfie wrote: post #60

One thing I wonder about hallucinations, is that it seems on the surface that it is an easy problem for RLVR to target. Since you're already generating enormous amounts of reasoning traces which are verified by correct answers, just have "don't know" as an option as a valid answer, and on problems where none of the thousands of reasoning traces led to a correct answer, just promote the traces that led to the "don't k…

Because nearly all benchmarks measure "accuracy" by giving you a point for a correct answer, and 0 points for everything else. If you have 100 questions you are 10% certain on, answering "I don't know" to all of those leads to 0 points, answering all of them as if you are confident leads to an expected value of 10 points. So that's what most AIs are trained to do AA-Omniscience is the only AI benchmark I know of wher…

AA-Omniscience Index gives +100 for correct, 0 for "I don't know" and -100 for incorrect.

For your scenario the confident confident strategy will give average of -90. Saying I dont't know to all will give 0.

A lot of models have negative AA-Omniscience Index.

They also do have AA-Omniscience Accuracy and AA-Omniscience Hallucination Rate that handle "I don't knows" differently.

https://artificialanalysis.ai/evaluations/omniscience

Re: GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2

#123

Post by coldtea »

wolttam wrote: post #113

> it is clear that actual intelligence has plateaued significantly. > Moving forward, the industry cannot continue to train bigger and bigger models since their intelligence not only plateaus but often will get worse These are wild claims - why are we concluding that bigger models and more data = more hallucination? That’s actually the opposite of what’s been happening over the last couple years. Some models may stil…

>These are wild claims - why are we concluding that bigger models and more data = more hallucination?

Because that's what they measured in this case.

Re: GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2

#124

Post by [deleted] »

amelius wrote: post #66
stalfie wrote: post #60

One thing I wonder about hallucinations, is that it seems on the surface that it is an easy problem for RLVR to target. Since you're already generating enormous amounts of reasoning traces which are verified by correct answers, just have "don't know" as an option as a valid answer, and on problems where none of the thousands of reasoning traces led to a correct answer, just promote the traces that led to the "don't k…

But if an LLM says "I don't know" should you pay for the tokens?

[deleted]

Re: GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2

#125

Post by ipaddr »

nutjob2 wrote: post #98
wongarsu wrote: post #95

Earlier quoted context omitted.

Because nearly all benchmarks measure "accuracy" by giving you a point for a correct answer, and 0 points for everything else. If you have 100 questions you are 10% certain on, answering "I don't know" to all of those leads to 0 points, answering all of them as if you are confident leads to an expected value of 10 points. So that's what most AIs are trained to do AA-Omniscience is the only AI benchmark I know of wher…

It should be 1 for correct, 0 for don't know and -1 for wrong. They are much better incentives. In real life a wrong answer is much more damaging than a don't know.

It should be -1, -.1, 1 because I don't know is slightly negative.

Re: GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2

#126

Post by eurekin »

wolttam wrote: post #113

> it is clear that actual intelligence has plateaued significantly. > Moving forward, the industry cannot continue to train bigger and bigger models since their intelligence not only plateaus but often will get worse These are wild claims - why are we concluding that bigger models and more data = more hallucination? That’s actually the opposite of what’s been happening over the last couple years. Some models may stil…

> A shift is happening among major AI labs, who are becoming increasingly skeptical of endless parameter count and training data scaling

I'm pretty sure it's mostly due to the training data quality. No idea, why this never gets mentioned in those discussions.

It was obvious right from the get go, that the scaling law just enabled some abilities, that were described by the underlying data and allowing the ANN to abstract it in the latent space.

Re: GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2

#127

Post by skinfaxi »

embedding-shape wrote: post #92
amelius wrote: post #66

Earlier quoted context omitted.

But if an LLM says "I don't know" should you pay for the tokens?

Depends on what your understanding of the product is. If someone sold you a "Solved all your problems" machine, and it suddenly doesn't solve all your problems, then probably no, you shouldn't pay. But the way I'm being sold LLMs, is basically "A text generator that gives your plausible-sounding human text that sometimes hallucinates and gets things wrong, based on your input", then regardless of what the outcome is,…

The marketing materials are very much the former though. From claude.com:

> If you can dream it, Claude can help you do it. Claude can process large amounts of information, brainstorm ideas, generate text and code, help you understand subjects, coach you through difficult situations, simplify your busywork so you can focus on what matters most, and so much more.

What marketing copy have you read for LLMs that is like you mentioned?

> But the way I'm being sold LLMs, is basically "A text generator that gives your plausible-sounding human text that sometimes hallucinates and gets things wrong, based on your input"

Re: GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2

#128

Post by ben_w »

realusername wrote: post #109
ben_w wrote: post #51

Earlier quoted context omitted.

I would say "only if you can review said work yourself alone", rather than "do". I'm an experienced developer, but I don't count myself as a web dev or a python dev; I can review the web and python stuff I get out of the AI (sometimes I need to ask the AI follow-up questions so I can find official documentation for what it did), but I can't write it.

I think you could eventually do it then, it would just take you longer.

If "eventually" counts, I can say I have "run" a marathon (I have walked that distance in one session, or if you don't like that verb I can sum all the various occasions I've run and that sum almost certainly exceeded 42.2 km before I finished school).

But the difference I allude to here is more like how "book reviewer" is a different job than "book author": yes, if you can review a book, you can also write one. Eventually.

Re: GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2

#129

Post by make3 »

cyanydeez wrote: post #65
stalfie wrote: post #60

One thing I wonder about hallucinations, is that it seems on the surface that it is an easy problem for RLVR to target. Since you're already generating enormous amounts of reasoning traces which are verified by correct answers, just have "don't know" as an option as a valid answer, and on problems where none of the thousands of reasoning traces led to a correct answer, just promote the traces that led to the "don't k…

the problem is the null answer will stop the "markov" chain. so, thats all.

Transformers are not Markovian, their whole point is arguably to be the reverse of Markovian, to efficiently make it so the new tokens are a function of all previous tokens

Re: GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2

#130

Post by hhhAndrew »

ipaddr wrote: post #125
nutjob2 wrote: post #98

Earlier quoted context omitted.

It should be 1 for correct, 0 for don't know and -1 for wrong. They are much better incentives. In real life a wrong answer is much more damaging than a don't know.

It should be -1, -.1, 1 because I don't know is slightly negative.

Interesting, I was about to say -1, 0.9, 1.0, because I don't know is almost as useful as the correct answer!
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