← All IntelClip / AI ToolsCurating English data improves non-English performance
From Data Quality Is the Compute Multiplier — Ari Morcos, DatologyAI · ≈11:20
A non-obvious cross-lingual transfer result, with the size of the effect correlating to a language's similarity to English — and a weaker effect in the reverse direction.
What’s in it
- A non-obvious cross-lingual transfer result, with the size of the effect correlating to a language's similarity to English — and a weaker effect in the reverse direction.
Clip transcript
want it to be. Um an interesting scientific result I want to share here is that we also see very strong cross-lingual benefits um from curation. Um so what's plotted here is the non-English accuracy um where in the the the left bar is showing not curating anything at all and then the right bar just curating the English. Um we also curate all the non-English data and that leads to much better performance. But I just want to show this because I think it's quite interesting that curating English data benefits non-English performance. Um and that's because we see this cross-lingual transfer where the model understands how English relates to say Spanish and and so therefore making it better at English would also make it better at Spanish to some extent and interestingly we see that the the um the size of magnitude of that transfer um is strongly correlated uh with the similarity between English and that language um and we also see it go the other way although the effects a bit smaller um where curating the non-English data also helps to benefit English data um performance
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