Method Drift›Parameter-efficient fine-tuning (LoRA family)
Superseded baseline#236 of 1,113 most-superseded
Laplace-LoRA
Parameter-efficient fine-tuning (LoRA family)
superseded — cited as a baseline and beaten by newer methods
2 papers critique it · 0 beat it on benchmarks
What papers say
Verbatim critique sentences, each from a paper that cites Laplace-LoRA as a baseline.
“Laplace-LoRA is a post-hoc calibration method requiring longer training iterations to bring the low-rank parameters from an unstable basin (a subspace associated with the same local optimum) to a more stable parametric space. Therefore, Laplace-LoRA often leads to sub-optimal downstream performance.”
— Robust and Efficient Fine-tuning of LLMs with Bayesian Reparameterization of Low-Rank Adaptation“Methods such as Laplace-LoRA~yang2023bayesian require an additional pass through the data to compute a Hessian or Fisher approximation.”
— Variational Low-Rank Adaptation Using IVON