It’s surprising to me that the ‘given’ setting fails so consistently across models when Anthropic models were found to do well at using gender pronouns equally (50%) c.f. my discussion here.
I suppose this means the capability demonstrated in that post was much more training data-specific and less generalizable than I had imaged.
Yes, it’s plausible to me that this capbility is data specific. E.g. It might also be better with “heads/tails” or “0/1″ because of examples of this in the training data.
It’s surprising to me that the ‘given’ setting fails so consistently across models when Anthropic models were found to do well at using gender pronouns equally (50%) c.f. my discussion here.
I suppose this means the capability demonstrated in that post was much more training data-specific and less generalizable than I had imaged.
Yes, it’s plausible to me that this capbility is data specific. E.g. It might also be better with “heads/tails” or “0/1″ because of examples of this in the training data.