31 citations · 109 across the 13 of their papers we have counts for
4 papers · 1 filter
Enhancing Multilingual Language Model with Massive Multilingual Knowledge Triples
Linlin Liu, Xin Li, Ruidan He +3
Knowledge-enhanced language representation learning has shown promising results across various knowledge-intensive NLP tasks. However, prior methods are limited in efficient utiliz…
MELM: Data Augmentation with Masked Entity Language Modeling for Low-Resource NER
Ran Zhou, Xin Li, Ruidan He +4
Data augmentation is an effective solution to data scarcity in low-resource scenarios. However, when applied to token-level tasks such as NER, data augmentation methods often suffe…
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…
Multi-Domain Active Learning: Literature Review and Comparative Study
Rui He, Shengcai Liu, Shan He +1
Multi-domain learning (MDL) refers to learning a set of models simultaneously, where each model is specialized to perform a task in a particular domain. Generally, a high labeling…