30% drop in O1-preview accuracy when Putnam problems are slightly variated

Post by fn-mote » Wed, Jan 01, 2025, 3:12 PM UTC

YetAnotherNick wrote: post #32

InkCanon wrote: post #10

Earlier quoted context omitted.

I've always assumed they removed it, because it's such a basic and fundamental part of ML training that you separate your test and train data. And yet I never see any papers even mention if/how they do this. And I wonder if they do, how do they guarantee with high reliability that their massive terabytes of data don't contain the answer.

First of all, Putnam is not in the test data, at least I haven't seen OpenAI claiming that publicly. Secondly, removing it from internet data is not 100% accurate. There are translations of the problems and solutions or references and direct match is not enough. MMLU and test set benchmarks show more resilience though in some previous research.

Post by whimsicalism » Wed, Jan 01, 2025, 3:13 PM UTC

fn-mote wrote: post #132

YetAnotherNick wrote: post #32

Earlier quoted context omitted.

First of all, Putnam is not in the test data, at least I haven't seen OpenAI claiming that publicly. Secondly, removing it from internet data is not 100% accurate. There are translations of the problems and solutions or references and direct match is not enough. MMLU and test set benchmarks show more resilience though in some previous research.

Let’s think about this. > Putnam is not in the test data, at least I haven't seen OpenAI claiming that publicly What exactly is the source of your belief that the Putnam would not be in the test data? Didn’t they train on everything they could get their hands on?

Post by [deleted] » Wed, Jan 01, 2025, 3:14 PM UTC

K0balt wrote: post #52

youworkwepay wrote: post #17

Or it's time to step back and call it what it is - very good pattern recognition. I mean, that's cool... we can get a lot of work done with pattern recognition. Most of the human race never really moves above that level of thinking in the workforce or navigating their daily life, especially if they default to various societally prescribed patterns of getting stuff done (eg. go to college or the military , find a job…

So, I am conflicted about this. If we take an example of what is considered a priori as creativity, such as story telling, LLMs can do pretty well at creating novel work. I can prompt with various parameters, plot elements, moral lessons, and get a de novo storyline, conflicts, relationships, character backstories, intrigues, and resolutions. Now, the writing style tends to be tone-deaf and poor at building tension f…

Post by whimsicalism » Wed, Jan 01, 2025, 3:17 PM UTC

YetAnotherNick wrote: post #32

InkCanon wrote: post #10

Earlier quoted context omitted.

I've always assumed they removed it, because it's such a basic and fundamental part of ML training that you separate your test and train data. And yet I never see any papers even mention if/how they do this. And I wonder if they do, how do they guarantee with high reliability that their massive terabytes of data don't contain the answer.

First of all, Putnam is not in the test data, at least I haven't seen OpenAI claiming that publicly. Secondly, removing it from internet data is not 100% accurate. There are translations of the problems and solutions or references and direct match is not enough. MMLU and test set benchmarks show more resilience though in some previous research.

Post by amluto » Wed, Jan 01, 2025, 3:18 PM UTC

wim wrote: post #49

One experiment I would love to see, although not really feasible in practice, is to train a model on all digitized data from before the year 1905 (journals, letters, books, broadcasts, lectures, the works), and then ask it for a formula for mass-energy equivalence. A certain answer would definitely settle the debate on whether pattern recognition is a form of intelligence ;)