Re:ChatGPT-4o vs. Math
by sabrina_ramonov on Thursday May 16, 2024 @02:02PM
(#40381326)
Yeah, like the other commenter mentioned, I could have run another experiment applying chain of thought specifically to the image interpretation. Just to force gpt to confirm its information extraction from the image. However, even after trying that approach, it got only 2/3 tries correct. Still superior is text only modality + chain of thought.
Re:ChatGPT-4o vs. Math
by flyingspaceship on Thursday May 16, 2024 @05:19PM
(#40383335)
The images bring with it their own unique set of problems. I was using it to help analyze UIs (before and after images) to determine if the changes I made were better or worse, but after using it for awhile I realized that it favored the second image in the comparison to an extent that made it difficult to tell which it thought was better. I suppose it's being trained on before and afters and generally the afters are always better!
But reading this I do have a thought: chain of thought, or guided thinking processes, really do help. I haven't been explicit in doing that for the image itself.
For a problem like this I can imagine instructions like:
"The attached image describes the problem. Begin by extracting any relevant information from the image, such as measurements, the names of angles or sides, etc. Then determine how these relate to each other and the problem statement."
Maybe there's more, or cases where I want it to do more "collection" before it does "determination". In some sense that's what chain-of-thought does: tell the model not to come to a conclusion before it's analyzed information. And perhaps go further: don't analyze until you've collected the information. Not unlike how we'd tell a student to attack a problem.