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Strong dislike for papers that tell me what to do in the title, especially when even the paper admits a loose correlation of the intermediate tokens compared to solution correctness. My solutions work and they speak for themselves.
From [1]: "Position papers make an argument for a viewpoint or perspective about what should be done [...]"
Strong dislike for papers that tell me what to do in the title, especially when even the paper admits a loose correlation of the intermediate tokens compared to solution correctness. My solutions work and they speak for themselves.
Pretty wild dressing a blog post up as a scientific paper.
Earlier quoted context omitted.
> The anthropomorphization of LLMs should be discouraged as much as possible. And yet, they have extensive human-like behavior. If you treat them nicely or encourage them, they perform better. Ignoring that human-like behavior is wrong headed.
I think you're ending that train of thought too early. Why does this occur? Well... We can hypothesize that these things are largely trained on internet dialogue so there's probably some correlation between threads where people are not flaming each other and the quality of the replies. They're just statistical engines so anything you can do to raise the odds of a helpful next token... I'm essentially just making shit…
Sheesh. Yes, I agree with you entirely. I'm merely pointing out that ignoring this behavior is dumb, too.
And probably not rationally based. Leads people to make crazy jumps. :)
Is anthropomorphizing a real problem? From what I know, none of the serious LLM researchers believe it has anything to do with human reasoning, apart from Anthropic with their click-baity terminology like "LLM biology". It's just a metaphor. "Reasoning tokens" is simpler to say than "learned prompt augmentation tokens". I used to (and still do) anthropomorphize things long before LLMs, and I've seen my colleagues do…
I have a coworker that spends at least 10 hours a week arguing with his like you would with a conscious person. I've gently tried to explain it's like arguing with your compiler for giving you an incoherent error message - it's pointless. It doesn't understand, it can't understand, and even if it could, you arguing with it isn't going to make it "learn" or act differently.
Strong dislike for papers that tell me what to do in the title, especially when even the paper admits a loose correlation of the intermediate tokens compared to solution correctness. My solutions work and they speak for themselves.
This is a position paper. Its purpose is to advocate for a specific viewpoint to the ML community. From [1]: "Position papers make an argument for a viewpoint or perspective about what should be done [...]" [1] https://icml.cc/Conferences/2026/CallForPositionPapers
Is anthropomorphizing a real problem? From what I know, none of the serious LLM researchers believe it has anything to do with human reasoning, apart from Anthropic with their click-baity terminology like "LLM biology". It's just a metaphor. "Reasoning tokens" is simpler to say than "learned prompt augmentation tokens". I used to (and still do) anthropomorphize things long before LLMs, and I've seen my colleagues do…
But some of the biggest evangelists, who are well respected programmers that get lauded on this very site, have said it is fully sentient and has emotions. Even going back to 2022, when the LLMs were dogshit, a Google employee lost his job claiming it was sentient because it said it had emotions.
Combine that with the marketing angle of both Anthropic and OpenAI, who have been trying their hardest to describe every function of an LLM as analogous to the human brain. Because it's politically useful to paint them as dangerous and uncontrollable, so the keys will only be granted to the few people on the mountaintop.
Earlier quoted context omitted.
> The anthropomorphization of LLMs should be discouraged as much as possible. And yet, they have extensive human-like behavior. If you treat them nicely or encourage them, they perform better. Ignoring that human-like behavior is wrong headed.
That's not a consequence of an LLM. It's a consequence of the training data. In fact, I would argue that the latest models aren't nearly as sensitive to the tone of input anymore. It's an issue that has been addressed by better curating training data.
https://www.anthropic.com/research/riemann-zeta
“Throughout this process, Jarred's input was mostly limited to sending Claude messages of encouragement (mostly variants of “keep going” or “believe in yourself”).2 This seems to have helped Claude overcome some initial skepticism that it could make meaningful progress.”
Is anthropomorphizing a real problem? From what I know, none of the serious LLM researchers believe it has anything to do with human reasoning, apart from Anthropic with their click-baity terminology like "LLM biology". It's just a metaphor. "Reasoning tokens" is simpler to say than "learned prompt augmentation tokens". I used to (and still do) anthropomorphize things long before LLMs, and I've seen my colleagues do…
Yes it's really a problem. On this website you are surrounded by people who have technical knowledge and understand at least somewhat, how a computer functions. You have the ability to separate "fun" and "reality" because you know you're putting input into a really really big calculator. Most people do not fathom this.
AI Psychosis is a real thing, look it up (don't just ask an LLM) and do some reading. It's actively harming people, and the way they think. There's no regulation around any of this stuff and it drives me crazy that we let these AI companies _sprint_ so far ahead of everyone, and now we're facing the consequences.