14 citations · 14 across the 2 of their papers we have counts for
3 papers
cs.CL2022
Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation
Qingyu Tan, Ruidan He, Lidong Bing +1
Document-level Relation Extraction (DocRE) is a more challenging task compared to its sentence-level counterpart. It aims to extract relations from multiple sentences at once. In t…
cs.CL2021★ 14 cited
On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation
Ruidan He, Linlin Liu, Hai Ye +6
Adapter-based tuning has recently arisen as an alternative to fine-tuning. It works by adding light-weight adapter modules to a pretrained language model (PrLM) and only updating t…
cs.CL2020
Feature Adaptation of Pre-Trained Language Models across Languages and Domains with Robust Self-Training
Hai Ye, Qingyu Tan, Ruidan He +3
Adapting pre-trained language models (PrLMs) (e.g., BERT) to new domains has gained much attention recently. Instead of fine-tuning PrLMs as done in most previous work, we investig…