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cs.CL2024
Gaussian Stochastic Weight Averaging for Bayesian Low-Rank Adaptation of Large Language Models
Emre Onal, Klemens Flöge, Emma Caldwell +2
Fine-tuned Large Language Models (LLMs) often suffer from overconfidence and poor calibration, particularly when fine-tuned on small datasets. To address these challenges, we propo…
cs.CL2021
Probing as Quantifying Inductive Bias
Alexander Immer, Lucas Torroba Hennigen, Vincent Fortuin +1
Pre-trained contextual representations have led to dramatic performance improvements on a range of downstream tasks. Such performance improvements have motivated researchers to qua…