4 papers
Bayesian-LoRA: Probabilistic Low-Rank Adaptation of Large Language Models
Moule Lin, Shuhao Guan, Andrea Patane +2
Large Language Models usually put more emphasis on accuracy and therefore, will guess even when not certain about the prediction, which is especially severe when fine-tuned on smal…
Flow-Induced Diagonal Gaussian Processes
Moule Lin, Andrea Patane, Weipeng Jing +2
We present Flow-Induced Diagonal Gaussian Processes (FiD-GP), a compression framework that incorporates a compact inducing weight matrix to project a neural network's weight uncert…
PreP-OCR: A Complete Pipeline for Document Image Restoration and Enhanced OCR Accuracy
Shuhao Guan, Moule Lin, Cheng Xu +5
This paper introduces PreP-OCR, a two-stage pipeline that combines document image restoration with semantic-aware post-OCR correction to enhance both visual clarity and textual con…
Stochastic Weight Sharing for Bayesian Neural Networks
Moule Lin, Shuhao Guan, Weipeng Jing +2
While offering a principled framework for uncertainty quantification in deep learning, the employment of Bayesian Neural Networks (BNNs) is still constrained by their increased com…