49 citations · 113 across the 23 of their papers we have counts for
4 papers · 1 filter
Examining Large Pre-Trained Language Models for Machine Translation: What You Don't Know About It
Lifeng Han, Gleb Erofeev, Irina Sorokina +2
Pre-trained language models (PLMs) often take advantage of the monolingual and multilingual dataset that is freely available online to acquire general or mixed domain knowledge bef…
Exploring the Value of Pre-trained Language Models for Clinical Named Entity Recognition
Samuel Belkadi, Lifeng Han, Yuping Wu +1
The practice of fine-tuning Pre-trained Language Models (PLMs) from general or domain-specific data to a specific task with limited resources, has gained popularity within the fiel…
Investigating Massive Multilingual Pre-Trained Machine Translation Models for Clinical Domain via Transfer Learning
Lifeng Han, Gleb Erofeev, Irina Sorokina +2
Massively multilingual pre-trained language models (MMPLMs) are developed in recent years demonstrating superpowers and the pre-knowledge they acquire for downstream tasks. This wo…
EDU-level Extractive Summarization with Varying Summary Lengths
Yuping Wu, Ching-Hsun Tseng, Jiayu Shang +3
Extractive models usually formulate text summarization as extracting fixed top- salient sentences from the document as a summary. Few works exploited extracting finer-grained El…