18 citations · 25 across the 8 of their papers we have counts for
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cs.CL2023
SlimFit: Memory-Efficient Fine-Tuning of Transformer-based Models Using Training Dynamics
Arash Ardakani, Altan Haan, Shangyin Tan +4
Transformer-based models, such as BERT and ViT, have achieved state-of-the-art results across different natural language processing (NLP) and computer vision (CV) tasks. However, t…
cs.CL2022
Benchmarking Language Models for Code Syntax Understanding
Da Shen, Xinyun Chen, Chenguang Wang +2
Pre-trained language models have demonstrated impressive performance in both natural language processing and program understanding, which represent the input as a token sequence wi…
cs.CL2022
PALT: Parameter-Lite Transfer of Language Models for Knowledge Graph Completion
Jianhao Shen, Chenguang Wang, Ye Yuan +5
This paper presents a parameter-lite transfer learning approach of pretrained language models (LM) for knowledge graph (KG) completion. Instead of finetuning, which modifies all LM…