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> You can get them to solve unseen problems just fine Prove that the problem wasn't seen by them in other form. > Specify a grammar in BNF notation and tell i

> You can get them to solve unseen problems just fine Prove that the problem wasn't seen by them in other form. > Specify a grammar in BNF notation and tell it to generate or parse sentences for you. You can produce a more than random enough grammar that it it can't have derived the parsing of it from past text, but necessarily reasons about BNF notation sufficiently well to be able to use it to deduce the grammar, and use that to parse subsequent sentences. You can have it analyse them and tag them according to the grammar to. And generate sentences. Oh, come on. It's like rewriting the same program in another programming language with different variables. What it can't do is to create a concept of programming language, I'm not talking about a new programming language, I'm talking about the concepts. > I'm sure that won't work for every problem of this sort, but the quality of tests people do on LLMs is really awful, at least because people tend to do very narrow tests like that and make broad pronouncements about what LLM's "can't" do based on it. Here, a few papers that show they can't reason: https://arxiv.org/abs/2311.00871 https://arxiv.org/abs/2311.00871 https://arxiv.org/abs/2309.13638 https://arxiv.org/abs/2309.13638 https://arxiv.org/abs/2311.09247 https://arxiv.org/abs/2311.09247 https://arxiv.org/abs/2305.18654 https://arxiv.org/abs/2305.18654 https://arxiv.org/abs/2309.01809 https://arxiv.org/abs/2309.01809

famouswaffles 2y ago
>It's like rewriting the same program in another programming language with different variables. Since when has that not required reasoning ? It's really funny seeing people bend over backwards to exclude LLMs from some imaginary "real reasoning" they imagine they are solely privy to. It's really obvious this is happening when they leave well defined criteria and branch into vague, ill-defined statements. What exactly do you mean by concepts ? Can you engineer some test to demonstrate what you're talking about ? Also, none of those papers show LLMs can't reason.
- lossolo 2y ago
  You clearly didn't read any of these papers. Quote from one of them "Our results support the hypothesis that GPT-4, perhaps the most capable “general” LLM currenly available, is still not able to robustly form abstractions and reason about basic core concepts in contexts not previously seen in its training data" Another, recent, good one https://arxiv.org/abs/2407.03321 https://arxiv.org/abs/2407.03321 EDIT: For people who don't want to read the papers, here is a blog post that explains what I'm arguing in more accessible terms https://cacm.acm.org/blogcacm/can-llms-really-reason-and-plan/ https://cacm.acm.org/blogcacm/can-llms-really-reason-and-pla...
  - famouswaffles 2y ago
    Oh i've read them. The claim doesn't match up to reality. It's as simple as that. You can claim anything you want to. https://arxiv.org/abs/2305.18354 https://arxiv.org/abs/2305.18354 All these papers you keep linking do is at best point out the shortcomings of current state of the art LLMs. They do not in any way disprove their ability to reason. I don't know when the word reason started having different standards for humans and machines but i don't care for it. Either your definition of reasoning also allows for the faulty kind humans display or humans don't reason either. You can't have your cake and eat it.
    - lossolo 2y ago
      > Oh i've read them. It's hard to believe that after reading all the papers and the blog I linked, along with the references there, any reasonable person would come to such strong conclusions as you did. This makes it hard for me to believe that you actually read all of them, especially given your previous questions and comments, which are addressed in those papers and someone that actually read them wouldn't make such comments or ask such questions. And the funniest thing, and further proof of this, is that you linked a paper that is addressed in one of the papers I shared. It seems like not only LLMs can fake things. > All these papers you keep linking do is at best point out the shortcomings of current state of the art LLMs They clearly show that they fake reasoning, and what they do is an advanced version of retrieval. Their claims are supported by evidence. What you call "shortcomings" are actually proof that they do not reason as humans do. It seems like your version of "reality" doesn't match reality.
      - famouswaffles 2y ago
        The paper i linked is not addressed by the paper you linked. The paper you linked attempts to give LLMs the same benchmarks in a format they aren't best suited for. I don't know how you can call that "addressed". >They clearly show that they fake reasoning Sure and planes are fake flying. The illusive "fake reasoning" that is so apparently obvious and yet does not seem to have a testable definition that excludes humans. You've still not explained how writing the same program in different languages doesn't require reasoning or how we can test your "correct" version of reasoning which requires "concepts".
vidarh 2y ago
> Prove that the problem wasn't seen by them in other form. You can reduce that risk to arbitrarily low levels by trying multiple random grammars of some complexity. This is a weak argument. > Oh, come on. It's like rewriting the same program in another programming language with different variables. No, it's like following a grammar, but that requires reasoning about a set of rules it has not seen before. I don't think you understood the task I described as well as ChatGPT does. > What it can't do is to create a concept of programming language, I'm not talking about a new programming language, I'm talking about the concepts. Neither can most humans. And have you tried to ask it about these concepts? I've had it infer semantics of code in programming languages that don't exist based on a hypothetical sample several times, and they're pretty good at coming up with semantics that makes sense. In one instance I gave it a sample with an idea about what made sense to me but it inferred a better set of semantics. None of the papers you linked supports your claim.

famouswaffles 2y ago

>It's like rewriting the same program in another programming language with different variables. Since when has that not required reasoning ? It's really funny seeing people bend over backwards to exclude LLMs from some imaginary "real reasoning" they imagine they are solely privy to. It's really obvious this is happening when they leave well defined criteria and branch into vague, ill-defined statements. What exactly do you mean by concepts ? Can you engineer some test to demonstrate what you're talking about ? Also, none of those papers show LLMs can't reason.

lossolo 2y ago
You clearly didn't read any of these papers. Quote from one of them "Our results support the hypothesis that GPT-4, perhaps the most capable “general” LLM currenly available, is still not able to robustly form abstractions and reason about basic core concepts in contexts not previously seen in its training data" Another, recent, good one https://arxiv.org/abs/2407.03321 https://arxiv.org/abs/2407.03321 EDIT: For people who don't want to read the papers, here is a blog post that explains what I'm arguing in more accessible terms https://cacm.acm.org/blogcacm/can-llms-really-reason-and-plan/ https://cacm.acm.org/blogcacm/can-llms-really-reason-and-pla...
- famouswaffles 2y ago
  Oh i've read them. The claim doesn't match up to reality. It's as simple as that. You can claim anything you want to. https://arxiv.org/abs/2305.18354 https://arxiv.org/abs/2305.18354 All these papers you keep linking do is at best point out the shortcomings of current state of the art LLMs. They do not in any way disprove their ability to reason. I don't know when the word reason started having different standards for humans and machines but i don't care for it. Either your definition of reasoning also allows for the faulty kind humans display or humans don't reason either. You can't have your cake and eat it.
  - lossolo 2y ago
    > Oh i've read them. It's hard to believe that after reading all the papers and the blog I linked, along with the references there, any reasonable person would come to such strong conclusions as you did. This makes it hard for me to believe that you actually read all of them, especially given your previous questions and comments, which are addressed in those papers and someone that actually read them wouldn't make such comments or ask such questions. And the funniest thing, and further proof of this, is that you linked a paper that is addressed in one of the papers I shared. It seems like not only LLMs can fake things. > All these papers you keep linking do is at best point out the shortcomings of current state of the art LLMs They clearly show that they fake reasoning, and what they do is an advanced version of retrieval. Their claims are supported by evidence. What you call "shortcomings" are actually proof that they do not reason as humans do. It seems like your version of "reality" doesn't match reality.
    - famouswaffles 2y ago
      The paper i linked is not addressed by the paper you linked. The paper you linked attempts to give LLMs the same benchmarks in a format they aren't best suited for. I don't know how you can call that "addressed". >They clearly show that they fake reasoning Sure and planes are fake flying. The illusive "fake reasoning" that is so apparently obvious and yet does not seem to have a testable definition that excludes humans. You've still not explained how writing the same program in different languages doesn't require reasoning or how we can test your "correct" version of reasoning which requires "concepts".

vidarh 2y ago

> Prove that the problem wasn't seen by them in other form. You can reduce that risk to arbitrarily low levels by trying multiple random grammars of some complexity. This is a weak argument. > Oh, come on. It's like rewriting the same program in another programming language with different variables. No, it's like following a grammar, but that requires reasoning about a set of rules it has not seen before. I don't think you understood the task I described as well as ChatGPT does. > What it can't do is to create a concept of programming language, I'm not talking about a new programming language, I'm talking about the concepts. Neither can most humans. And have you tried to ask it about these concepts? I've had it infer semantics of code in programming languages that don't exist based on a hypothetical sample several times, and they're pretty good at coming up with semantics that makes sense. In one instance I gave it a sample with an idea about what made sense to me but it inferred a better set of semantics. None of the papers you linked supports your claim.