Active Fine Tuning
The discussion highlights the significance of transductive active fine tuning as a legitimate approach to enhancing model generalization. François argues that while human supervision is involved in programming, the process of using demonstration pairs for fine-tuning is largely autonomous. Both speakers explore the intricacies of adapting models to novel tasks, emphasizing the importance of knowledge recombination in achieving effective adaptation.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Francois Chollet - ARC reflections - NeurIPS 2024
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