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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

#91
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 main problem here is that hallucination suppression doesn’t generalise. We can penalise models for incorrect answers on a wide range of questions, but this doesn’t lead to the emergence of a coherent worldview, which, coupled with logical abilities, is the only true remedy against hallucinations. With current architectures, hallucinations will likely persist on open-domain tasks forever.

> We can penalise models for incorrect answers on a wide range of questions, but this doesn’t lead to the emergence of a coherent worldview, which, coupled with logical abilities, is the only true remedy against hallucinations

I don't think anyone is trying to add "a coherent worldview" by reducing hallucinations, not sure how that even realistically could be aim.

What people want, is for the models to stop giving confident answers that are clearly incorrect. Yes, it won't lead to "a coherent worldview", but it'll at least stop wasting people's time if the model said "You know what, what you said doesn't make sense / isn't clear, is what you mean .... ?" or even "I'm not sure" or "I don't know".

Currently, if you have the wrong starting point, ask the model to do something, they more often than not just go ahead and do that, misunderstandings or not. They seem optimized to never push back, unless you prompt for that, and most seem to favor "I'm just gonna assume X" rather than taking a step back and figuring out how to not assume. Again, unless you prompt against that behaviour/steering it into a different workflow.

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

#92
post #66
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?

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, I still made use of the "Input > Output" part, which is what I bought into, so I should still pay for that.

Now of course bunch of people will say they been sold the former, but the companies themselves seem to be selling the latter. That's my perspective from a person who doesn't follow "influencers" and what not though, which seem to be selling the public on the former rather than the latter.

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

#93
post #82

Earlier quoted context omitted.

If you had an llm that could accurately predict when a claim is uncertain it would be very popular, I think. I would pay for that kind of reliability tbh

This would break reality. There’s some underlying physical law that prevents the existence of any algorithm of truth.

> There’s some underlying physical law that prevents the existence of any algorithm of truth

Haven't heard about that law, but seems unlikely we can come up with ("discover") any sort of law that uses a concept ("truth") humans can't even agree what it means, and that's not for a lack of trying, we've been trying to figure it out for millenniums already with no end in sight.

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

#94

> 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. DeepSeek V4 Pro (1.6T params, 49B active, 44 AA Intelligence Index score) has a ludicrous 94% hallucination score on the AA-Omniscience benchmark, meaning on questions that it couldn’t figure out, it only stated that it didn’t know around 6% of the time, and the rest it conf…

There is no concept of "knowledge" in LLM as it is on Wikipedia.

The question-tokens define the answer-tokens. That's it. The art relies in clustering the relevant weights together.

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

#95
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 where randomly guessing gets you a lower average score than answering all questions with "I don't know"

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

#96
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…

It’s not as simple. I trained an LLM before on exactly this, to scratch the itch of this question.

The task was simple, using the MS-MARCO[0] dataset which contains queries, search results, answers, I made a training set that has:

1. Questions paired with real results supporting them (mixed with some irrelevant results), and a correct answer

2. Questions paired only with irrelevant results, with the answer “No answer present”

The dataset was huge (close to 1M samples), and I trained using different techniques, from SFT (just mimicking the dataset) to DPO (good answer contrasted with a bad answer for the same user query) to GRPO (verifier that checks my annotations whether an answer was present or not)

Lo and behold, this didn’t reduce hallucination, rather made it much worse. Now the model started claiming “No answer present” even when it is, or even when the question didn’t need search results in the first place (simple stuff like what is X+Y).

Now you could argue that my training was basic compared to what frontier labs could do. Yet I think it hints at a more profound limitation. LLMs are finicky and don’t have a neat understand of things from first principles (list of search results, check relevance of result to user query, if answers are below a certain threshold of relevance then don’t consider them to answer …).

tl;dr: not as simple as one might think, perhaps not attainable at all.

0: https://huggingface.co/datasets/microsoft/ms_marco

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

#97
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…

If we had a theoretical technique to identify the true and objective reality we'd use it in the courts and laboritories. There is no such technique, but what we do have is 2 techniques that seem work:

1) Has a certain standard of evidence been met?

2) Are the related arguments free of logical inconsistencies?

We can train the LLMs to do 2, and maybe even 1 to some extent (exactly what quality of evidence a computer can practically gather is limited). But that isn't going to get rid of hallucinations, for the same reason courts are hit-and-miss or the conclusions of studies often aren't very reliable. These techniques help, but sometimes they still get people to say things that, on close inspection, turn out to be nonsense. And those best-effort approaches are too much to expect for most questions an LLM will be handed which are informal, low stakes and don't need strong supporting evidence or logical rigour.

I think it is underestimated how many LLM-style hallucinations people themselves have. It just isn't obvious because most humans have a strategy of only repeating what the herd says after it has been socially vetted, which makes their individual eccentricities less obvious.

TLDR; I don't think it looks like an easy problem for RLVR, it looks technically unsolvable. Even making progress requires a philosophical breakthrough on the nature of truth so that the objective function can be established.

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

#98
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…

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.

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

#99
post #66
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?

'I don't know' is the correct answer for infinitley more questions than those that can be answered.

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

#100
post #75

Earlier quoted context omitted.

Why not? It did the work. Why should you expect it to be omniscient? We can rank them based on how much they know and people will gravitate towards those that do know more. It's a market after all.

If it’s a market, wouldn’t the incentive be to lie about knowing and thus to keep the hallucinations?

According to your logic the market will produce an LLM that consists only of 'PRINT "I don't know."'.
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