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SUMMARY:New directions in synthetic data
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: Tatsunori Hashimoto\, Stanford \nTitle: New directions in synthetic data \nAbstract: Synthetic data has been an effective\, if boring set of techniques: prompt some language model to restructure your corpus to match some downstream task\, with occasionally some distillation. In this talk\, we will take a more expansive view of synthetic data as a general algorithmic tool for generative modeling\, arguing that the design space and possibilities of synthetic data are much bigger than it might seem. Through a few recent works\, we will show that synthetic data has major benefits beyond transforming the data – improving in-domain perplexities\, and enabling unique algorithmic primitives\, such as neighborhood smoothing and concatenated ‘mega’ documents. With this broader view\, we will point towards a nascent but interesting possibility of treating data itself as an algorithmic object to be engineered and optimized end-to-end. \n 
URL:https://cmsa.fas.harvard.edu/event/newtech_5626/
LOCATION:Virtual
CATEGORIES:New Technologies in Mathematics Seminar
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-NTM-Seminar-5.6.2026.docx.png
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