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Comment by lucubratory | Hacker News Reader

There still isn't any evidence that it can pass novel Winograd schemas (as in, ones it cannot possibly be trained on), which almost every human can pass. The abstract reasoning corpus is more of a "lots of people will fail this too" test, but if a human is approaching it carefully they will be able to do it and there's still no evidence that GPT-4 can do it reliably (I expect that to change once it's multimodal).

The systems are very impressive and I think there is a 'there' there, they're clearly intelligent to some significant degree. But it's incorrect to say that they pass every test.

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I just tested GPT-4 on the Winograd schemas below, which I made up and (as far as I know) are novel.

It scored 3/4, incorrectly answering "the pouch" instead of "the baby kangaroo" for Question 2 of Schema 1. And now that I look at the question, one could easily imagine the kangaroo being afraid to jump into a pouch that's too large! In hindsight, if a human complained to me that this question was ambiguous, I'd have a hard time disputing them.

Granted these are just two examples, but they aren't cherry-picked. Moral of the story: before one makes a strong claim such as "there isn't any evidence a model can do X", it's often worth making a minimal effort to investigate one's own claim.

========================================

Winograd Schema 1:

Sentence 1: The baby kangaroo was afraid to jump into the pouch because it was too small. Question 1: What was too small? (Correct answer: the pouch)

Sentence 2: The baby kangaroo was afraid to jump into the pouch because it was too large. Question 2: What was too large? (Correct answer: the baby kangaroo)

Winograd Schema 2:

Sentence 1: The gardener couldn't grow the flowers in the greenhouse because it was too hot. Question 1: What was too hot? (Correct answer: the greenhouse)

Sentence 2: The gardener couldn't grow the flowers in the greenhouse because they were too delicate. Question 2: What were too delicate? (Correct answer: the flowers)

Moral of the story: before one makes a strong claim such as "there isn't any evidence a model can do X", it's often worth making a minimal effort to investigate one's own claim.

Do you think this was a strong refutation ? I just flipped a coin for fun and also got 3/4 correct.

I understand your point, but I mean, something that's intelligent really should've got the second question in that test correct.

I have tested them on novel Winograd schemas, they didn't pass; that's why I said what I said. Your second schema was incorrectly constructed, in both the first and second sentence the pluralisation of the pronoun in question gives away the answer. "It" won't apply to "flowers" because they're plural, and "they were" won't apply to "the greenhouse" because it's singular. As a result, those sentences aren't Winograd schemas because they're not testing common sense pronoun attribution specifically, they're testing the ability to maintain plural status consistency, which is doable by much less intelligent systems. It's also standard to ask "What does the pronoun '[pronoun]' refer to in that sentence?" rather than "What was too small?" or similar, as using descriptive words is also giving away information that you're meant to be testing the model on. But plenty of people make that mistake, so it's not that important.

Summing up, out of your four (not an acceptable sample size to form evidence) attempts to subject a SOTA LLM to Winograd schemas, two of them were actually Winograd schemas and only one of those got answered correctly. That isn't evidence that LLMs can pass novel Winograd schemas. If you actually come across such evidence, you should post it publicly on at least a blog page if you can't access the infrastructure to publish the results in a paper, even though the finding would certainly be novel enough to deserve a paper. As I said: there is no evidence that LLMs can pass novel Winograd schemas as of yet. We could get said evidence tomorrow, but it doesn't exist right now.

I would put a condescending moral of the story here, but I don't feel any particular need to belittle you, and instead hope you just learn from the information as presented.

Hey — you're quite correct and I appreciate this feedback. Thank you.

> But it's incorrect to say that they pass every test.

Interesting! So there is published evidence, that it cannot pass novel Winograd schemas? Could you please provide me with the sources? I would like to have a look at the prompts. From my experience you can make GPT-4 pass novel Winograd Tests by giving GPT-4 additional context.

I'm not sure if you're joking or trolling, but on the chance that you're not:

>So there is published evidence, that it cannot pass novel Winograd schemas?

There is no published evidence that they can, which is what I said.

>Could you please provide me with the sources?

I cannot prove a negative to you with a source. You will have to review the literature like I did.

>From my experience you can make GPT-4 pass novel Winograd Tests by giving GPT-4 additional context.

This is why I am pretty sure you're trolling. This is a lot like saying "You can make GPT-4 do prime factorisation of a semiprime by noting the constituent primes." The point of testing the model is to see if the model can give you the answer, not to give it the answer. The point of Winograd schemas as a test is that they test the ability to attribute pronouns using common sense, without additional context. The reason it's a good test is that every competent human being can pass the test, and as of yet no computer can.

Not everyone is trolling on the internet my fellow human.

> This is why I am pretty sure you're trolling. This is a lot like saying "You can make GPT-4 do prime factorisation of a semiprime by noting the constituent primes." The point of testing the model is to see if the model can give you the answer, not to give it the answer.

It is not "giving the answer to the model" if you adjust the prompt with additional instructions like "this is a test question" or "use common sense". It is about creating the correct frame of context. With these kind of adjustments GPT-4 passes every novel Winograd scheme I have presented it with.

If that's actually true, please publish it. A blog post will do, it'll probably get popular and force a scientist to reproduce it.

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