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cs.LG2026
Categorical Prior Lock-in: Why In-Context Learning Fails for Structured Data
Antonio Pelusi, Stefano Braghin, Alberto Trombetta
Large language models (LLMs) are increasingly used as conditional generators for structured data, relying on in-context learning (ICL) to adapt to new distributions without paramet…
cs.LG2022
Robust Learning Protocol for Federated Tumor Segmentation Challenge
Ambrish Rawat, Giulio Zizzo, Swanand Kadhe +2
In this work, we devise robust and efficient learning protocols for orchestrating a Federated Learning (FL) process for the Federated Tumor Segmentation Challenge (FeTS 2022). Enab…