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Reframing Data Value for Large Language Models Through the Lens of Plausibility
Mohamad Rida Rammal, Ruida Zhou, Suhas Diggavi
Data valuation seeks to answer the important question, "How much is this data worth?" Existing data valuation methods have largely focused on discriminative models, primarily exami…
An Information-Theoretic Approach to Understanding Transformers' In-Context Learning of Variable-Order Markov Chains
Ruida Zhou, Chao Tian, Suhas Diggavi
We study transformers' in-context learning of variable-length Markov chains (VOMCs), focusing on the finite-sample accuracy as the number of in-context examples increases. Compared…
ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning
Kaan Ozkara, Bruce Huang, Ruida Zhou +1
Statistical heterogeneity of clients' local data is an important characteristic in federated learning, motivating personalized algorithms tailored to the local data statistics. Tho…