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> 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 suite

> 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". What you're writing now is nonsense in context of what I wrote. Once again, you're showing that you didn't read the papers. Which paper are you even referring to now, the one you think addresses the paper you linked? > 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". "Concepts" are explained in one of the papers I linked, which you would know if you had actually read them. As to programming languages they learn to identify common structures and idioms across languages. This allows them to map patterns (latent space representations duh!) from one language to another without reasoning about the underlying logic. When translating code, the model doesn't reason about the program's logic but predicts the most likely equivalent constructs in the target language based on the surrounding context. LLMs don't truly "understand" the semantics or purpose of the code they're translating. They operate on a superficial level, matching patterns and structures without grasping the underlying computational logic. The translation process for an LLM is a series of token-level transformations guided by learned probabilities, not a reasoned reinterpretation of the program's logic. They don't have an internal execution model or ability to "run" the code mentally. They perform translations based on learned patterns, not by simulating the program's behavior. The training objective of LLMs is to predict the next token, not to understand or reason about program semantics. This approach doesn't require or develop reasoning capabilities.

famouswaffles 2y ago
You are making a lot of assumptions that are mostly wrong. Case in point: https://arxiv.org/abs/2305.11169 https://arxiv.org/abs/2305.11169 I'm asking for something testable, not some post-hoc rationalization you believe to be true. I'm not asking you to tell me how you think LLMs work. I'm asking you to define "real reasoning" such that i can test people and LLMs for it and distinguish "real reasoning" from "fake reasoning". This definition should include all humans while excluding all LLMs. If it cannot, then it's just an arbitrary distinction.
- HAL3000 2y ago
  It appears that you are the only person in this discussion making many incorrect assumptions. Based on your comments, I would assume you are actually googling those papers based on their abstracts. Your last linked paper has flawed methodology for what it attempts to demonstrate, as shown in this paper: https://arxiv.org/pdf/2307.02477 https://arxiv.org/pdf/2307.02477 The tests you're requesting are provided within the previously linked papers. I'm not sure what you want. Do you expect people to copy and paste entire papers here that show methodology and describe experiments? You wrote, "I'm asking you to define 'real reasoning'," which is actually defined in the blog post linked earlier in this discussion. In fact, the entire blog post is about this topic. It appears that you are not thoroughly reading the material. Your replies resemble those of a human stochastic parrot.
  - famouswaffles 2y ago
    >Your last linked paper has flawed methodology for what it attempts to demonstrate, as shown in this paper: https://arxiv.org/pdf/2307.02477 https://arxiv.org/pdf/2307.02477 Genuinely, What's wrong with the methodology? Your paper literally admits humans would also perform worse at counterfactuals. Worse than a LLM ? Maybe not but it never bothers to test this so... The problem here is that none of the definitions (those that are testable) so far given actually separate humans from LLMs. They're all tests some humans would also flounder at or that LLMs perform far greater than chance at, if below some human's level. If you're going to say, "LLMs don't do real reasoning because of x" then x better be something all humans clear if what humans do is "real reasoning". Humans perform worse at counterfactuals so saying "Hey, see this paper that shows LLMs doing the same, It means they don't reason" is a logical fallacy if you don't extend that conclusion to humans as well.
    - vidarh 2y ago
      In these arguments it's always very notable that not only do people not benchmark LLMs against people, but several I've discussed with have argued very strongly for not doing so unless they're benchmarked against above average people. While arguing that these same tests prove LLMs can reason. It never seems to land with them that their standards for "reason" would exclude large portions of the human population to some state of lesser being without the ability to reason.

famouswaffles 2y ago

You are making a lot of assumptions that are mostly wrong. Case in point: https://arxiv.org/abs/2305.11169 https://arxiv.org/abs/2305.11169 I'm asking for something testable, not some post-hoc rationalization you believe to be true. I'm not asking you to tell me how you think LLMs work. I'm asking you to define "real reasoning" such that i can test people and LLMs for it and distinguish "real reasoning" from "fake reasoning". This definition should include all humans while excluding all LLMs. If it cannot, then it's just an arbitrary distinction.

HAL3000 2y ago
It appears that you are the only person in this discussion making many incorrect assumptions. Based on your comments, I would assume you are actually googling those papers based on their abstracts. Your last linked paper has flawed methodology for what it attempts to demonstrate, as shown in this paper: https://arxiv.org/pdf/2307.02477 https://arxiv.org/pdf/2307.02477 The tests you're requesting are provided within the previously linked papers. I'm not sure what you want. Do you expect people to copy and paste entire papers here that show methodology and describe experiments? You wrote, "I'm asking you to define 'real reasoning'," which is actually defined in the blog post linked earlier in this discussion. In fact, the entire blog post is about this topic. It appears that you are not thoroughly reading the material. Your replies resemble those of a human stochastic parrot.
- famouswaffles 2y ago
  >Your last linked paper has flawed methodology for what it attempts to demonstrate, as shown in this paper: https://arxiv.org/pdf/2307.02477 https://arxiv.org/pdf/2307.02477 Genuinely, What's wrong with the methodology? Your paper literally admits humans would also perform worse at counterfactuals. Worse than a LLM ? Maybe not but it never bothers to test this so... The problem here is that none of the definitions (those that are testable) so far given actually separate humans from LLMs. They're all tests some humans would also flounder at or that LLMs perform far greater than chance at, if below some human's level. If you're going to say, "LLMs don't do real reasoning because of x" then x better be something all humans clear if what humans do is "real reasoning". Humans perform worse at counterfactuals so saying "Hey, see this paper that shows LLMs doing the same, It means they don't reason" is a logical fallacy if you don't extend that conclusion to humans as well.
  - vidarh 2y ago
    In these arguments it's always very notable that not only do people not benchmark LLMs against people, but several I've discussed with have argued very strongly for not doing so unless they're benchmarked against above average people. While arguing that these same tests prove LLMs can reason. It never seems to land with them that their standards for "reason" would exclude large portions of the human population to some state of lesser being without the ability to reason.