204 citations · 388 across the 43 of their papers we have counts for
4 papers · 1 filter
HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning
Chunlin Tian, Zhan Shi, Zhijiang Guo +2
Adapting Large Language Models (LLMs) to new tasks through fine-tuning has been made more efficient by the introduction of Parameter-Efficient Fine-Tuning (PEFT) techniques, such a…
Inflected Forms Are Redundant in Question Generation Models
Xingwu Sun, Hongyin Tang, chengzhong Xu
Neural models with an encoder-decoder framework provide a feasible solution to Question Generation (QG). However, after analyzing the model vocabulary we find that current models (…
Improving Pre-trained Language Model Fine-tuning with Noise Stability Regularization
Hang Hua, Xingjian Li, Dejing Dou +2
The advent of large-scale pre-trained language models has contributed greatly to the recent progress in natural language processing. Many state-of-the-art language models are first…
Noise Stability Regularization for Improving BERT Fine-tuning
Hang Hua, Xingjian Li, Dejing Dou +2
Fine-tuning pre-trained language models such as BERT has become a common practice dominating leaderboards across various NLP tasks. Despite its recent success and wide adoption, th…