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Personalized skills for coding agents may not be the silver bullet developers hoped for, as generic skills often deliver superior performance.
Learning to coordinate retrieval signals can significantly boost multi-hop reasoning accuracy in language models.
Forget generic student models – this work shows you can get significantly more realistic student simulations by conditioning on a student's full learning history, unlocking better tutor model training and evaluation.
