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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

#51

Post by ben_w »

realusername wrote: post #19
gymbeaux wrote: post #17

Earlier quoted context omitted.

Those numbers are abysmal. Should we really be using LLMs to write our code? I have a theory- LLMs can spit out code that gets the job done and looks ok, maybe even great, but contains small “anomalies” that compound over time. An enterprise app developed entirely with LLM-happy devs might end up virtually unmaintainable. I’m not sure how to explain it, but the more I see LLM-written code the more I feel it’s bad cod…

> code that gets the job done and looks ok, maybe even great, but contains small “anomalies” that compound over time They clearly are only assistants for the moment, you can use them to do work ... but only if you could do the said work yourself alone in the first place.

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.

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

#54

Post by oshrimpton »

wiether wrote: post #52

Purely anecdotal, but when OpenAI removed Codex-5.3 from the ChatGPT sub and forced me to move to GPT-5.5, the result was far worse than what I was enjoying with Codex. And, of course, it was burning 10 times more tokens for this output.

Yeah they are 100% in the wrong for removing the fine tuned codex models. It makes sense why they wouldn't want to allocate so many resources towards fine tuning but still the enshittification of GPT models is real

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

#55

Post by andybak »

gymbeaux wrote: post #17
aesthesia wrote: post #4

Hallucination rate scores are a little tricky to interpret because they're conditional on the model not knowing the answer. That means they don't measure the probability of your encountering a hallucination in everyday use, since that also depends on the probability of the model not knowing the answer, as well as how well your distribution of tasks aligns with the distribution tested in the eval. I'd also hesitate to…

Those numbers are abysmal. Should we really be using LLMs to write our code? I have a theory- LLMs can spit out code that gets the job done and looks ok, maybe even great, but contains small “anomalies” that compound over time. An enterprise app developed entirely with LLM-happy devs might end up virtually unmaintainable. I’m not sure how to explain it, but the more I see LLM-written code the more I feel it’s bad cod…

I can't help but feel that people continually underestimate how bad human written code becomes over time. The exception is probably single-person passion projects or open source projects that maintain quality governance over time.

I strongly suspect most closed source code developed under commercial or internal pressure is pretty awful after a few years of development.

All LLM code has to do is suck less than existing code. And that's presuming the code quality doesn't improve as the models, the harnesses and our ways of working with them improve.

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

#56

Post by master-lincoln »

spwa4 wrote: post #37

Why is everyone expecting LLMs to be like the Star Trek computer? I wonder if anyone's ever measured what the hallucination rate of a human is.

Yeah it has been looked at e.g. in [0]. They separate that from lying, but I think for the LLM context it should be included. To me the difference is humans do not bullshit at the same rate and I can find out over time who tends to bullshit more and exclude that persons info from my pool.

> Why is everyone expecting LLMs to be like the Star Trek computer?

Because they are often marketed as magic AIs, not as mere language models.

[0] https://bpspsychub.onlinelibrary.wiley.com/doi/10.1111/bjso....

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

#57

Post by fvv »

wiether wrote: post #52

Purely anecdotal, but when OpenAI removed Codex-5.3 from the ChatGPT sub and forced me to move to GPT-5.5, the result was far worse than what I was enjoying with Codex. And, of course, it was burning 10 times more tokens for this output.

I have the opposite experience with codex 5.3 I had to use 5.2 to design and 5.3-codex to execute , while 5.4 was a better in both, and 5.5 ( all used xhigh) is even better

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

#58

Post by baq »

ben_w wrote: post #48
VBprogrammer wrote: post #46

Earlier quoted context omitted.

> Can there be bugs? Sure. That's the price of not reading or understanding every line. I've yet to come across a human developer who's output would meet this standard, despite writing every line. In fact, having an LLM review our code is catching quite a few bugs before it reaches QA.

Indeed, though I find the distribution is different. The humans may skip unit tests and need reminding; the AI always write unit tests once it's in AGENTS.md or whatever, but my experience* was that 5-10% of the time the LLM's attempt at a "test" would, instead of executing the code and examining the results, open the source code as a text file and run a regex to find/exclude certain substrings . * At the start of th…

I’ve been piloting LLMs for the past six months non stop and we’re at the point where formally verified models generated as an intermediate step between spec and code are very good value.

Riding the exponential means you have to update priors more often.

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

#59

Post by boofus »

m3h wrote: post #28
taffydavid wrote: post #25

> For the non technical, this is like asking a delivery driver to drop off packages at 3 houses at the same time without ever stopping the truck. I'm already hallucinating about how this could work and it involves catapults

Or we could simply hallucinate that the packages are there at the three houses. Hallucinations all the way down...

Nobody said the 3 houses needed to be on separate properties. Just throw the 3 packages from the moving truck at the one address where all 3 live.

Being an LLM is easy!

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

#60

Post by stalfie »

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 know" answer as training data. Essentially teaching the model that "I don't know" is a valid answer.

Sam Altman himself had a blog post about this a while ago that seemed to suggest this thought, so I guess it's obvious to everyone. But if that is so I assume it's just not as easy in practice.

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