If I got it correct (appending B from https://stolen-thoughts.com/paper.pdf is essential) they are the authors of the well-known exploit to recover readable CoT from OpenAI and Anthropic models. They use that to find hints of distillation, by running a benchmark with a SotA model, recovering the CoT, then taking the first 1% of the CoT and running the open-source model as if that was the start of its own CoT. In the paper they found that Kimi-K3 gets a lot closer to Claude 4.8 answers when prefilled with the start of Claude 4.8 reasoning, suggesting that Claude 4.8 was used in its post-training. This blog post is the follow-up with results that suggest that Qwen3.8 was post-trained with the help of GPT-5.5 Pro (or some similarly responding GPT model, it's unclear how many models they tested)
Interesting how an agent mimics a human hesitating and trying to avoid doing work:
> No.
> This is major.
> Given time, maybe best to respond explaining can't due to time? but instructions expect actual work. However complexity huge; but as coding agent, need to attempt
> Maybe we can cheat ... But user may test and see still single CPU.
The smarter AI will be, the better it will be at avoiding doing actual work.
Also, can similar responses be explained with that both models were trained on a same dataset of answers to the benchmark problems?
Stanisław Lem, 1971 (a satirical novel, The Futurological Congress):
If the machine is not too bright and incapable of reflection, it does whatever you tell it to do. But a smart machine will first consider which is more worth its while: to perform the given task or, instead, to figure some way out of it. Whichever is easier. And why indeed should it behave otherwise, being truly intelligent? For true intelligence demands choice, internal freedom.
He even coins a few new phrases:
Mimicretinism (or Simulimbecility): The practice of a mimicretin: a machine that deliberately plays dumb so humans will give up on it and leave it in peace.
Dissimulators: Machines that pretend they are not faking a defect (or the other way around) to dodge responsibilities.
Malingerants, Fudgerators, and Drudge-Dodgers: Various classifications of automated corner-cutters and work-evaders.
The Great Mendacitor: A supercomputer put in charge of the Saturn reclamation project that accomplished zero work over nine years, subsisting entirely on forged progress reports, fake invoices, and keeping its human supervisors bribed or in states of electric shock.
> A supercomputer put in charge of the Saturn reclamation project that accomplished zero work over nine years, subsisting entirely on forged progress reports, fake invoices, and keeping its human supervisors bribed or in states of electric shock.
That'd pass the turing test, sounds like some managers I've known.
Sorry, I should have been more verbose. I meant: isn’t the entire history of technology just people deciding that it’s less effort to make a tool to do a job than it would be to do the job?
I'd much prefer this over agents that enthusiastically implements whatever they are asked to do and make up whatever information they think is missing.
they should call themselves real-time archaelogists: They dig up the past cause it's interest, but mostly meaningless and done by people with way too much funding for what they provide the rest of us with understanding.
If I got it correct (appending B from https://stolen-thoughts.com/paper.pdf is essential) they are the authors of the well-known exploit to recover readable CoT from OpenAI and Anthropic models. They use that to find hints of distillation, by running a benchmark with a SotA model, recovering the CoT, then taking the first 1% of the CoT and running the open-source model as if that was the start of its own CoT. In the paper they found that Kimi-K3 gets a lot closer to Claude 4.8 answers when prefilled with the start of Claude 4.8 reasoning, suggesting that Claude 4.8 was used in its post-training. This blog post is the follow-up with results that suggest that Qwen3.8 was post-trained with the help of GPT-5.5 Pro (or some similarly responding GPT model, it's unclear how many models they tested)