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cs.LG2025
Meta-Learning at Scale for Large Language Models via Low-Rank Amortized Bayesian Meta-Learning
Liyi Zhang, Jake Snell, Thomas L. Griffiths
Fine-tuning large language models (LLMs) with low-rank adaptation (LoRA) is a cost-effective way to incorporate information from a specific dataset. However, when a problem require…
cs.LG2025
Conformal Prediction as Bayesian Quadrature
Jake C. Snell, Thomas L. Griffiths
As machine learning-based prediction systems are increasingly used in high-stakes situations, it is important to understand how such predictive models will perform upon deployment.…