AI RESEARCH
Meta-Learning at Scale for Large Language Models via Low-Rank Amortized Bayesian Meta-Learning
arXiv CS.LG
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ArXi:2508.14285v3 Announce Type: replace 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 requires incorporating information from multiple datasets - as in few shot learning - generalization across datasets can be limited, driving up