On Task Performance and Model Calibration with Supervised and Self-Ensembled In-Context Learning
The article provides an in-depth analysis of In-Context Learning (ICL) and Supervised Fine-Tuning (SFT), two predominant methodologies in machine learning. The authors highlight a common problem with these methods: overconfidence…
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