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Interactive Learning
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FDS Workshop: AI for Social Science Research Methods
Social scientists are increasingly incorporating AI into their designs, data collection, analyses, and workflows. Alongside rapid adoption, important methodological questions remain: What are the principled approaches to validating measurements via AI tools? To what extent are AI-generated observations interchangeable with those from human respondents — and what does that mean for the future of survey…
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S&DS Seminar: Zhuoran Yang (Yale), “Unveiling In-Context Learning: Provable Training Dynamics and Feature Learning in Transformers”
Abstract: In-context learning (ICL) is a cornerstone of large language model (LLM) functionality, yet its theoretical foundations remain elusive due to the complexity of transformer architectures. In particular, most existing work only theoretically explains how the attention mechanism facilitates ICL under certain data models. It remains unclear how the other building blocks of the transformer contribute…