activity
20202025
most citedA Pattern-mining Driven Study on Differences of Newspapers in Expressing Temporal Information

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2025

A Survey of QUD Models for Discourse Processing

Yingxue Fu

Question Under Discussion (QUD), which is originally a linguistic analytic framework, gains increasing attention in the community of natural language processing over the years. Var…

cs.CL2024

Automatic Alignment of Discourse Relations of Different Discourse Annotation Frameworks

Yingxue Fu

Existing discourse corpora are annotated based on different frameworks, which show significant dissimilarities in definitions of arguments and relations and structural constraints.…

cs.CL2023

Discourse Relations Classification and Cross-Framework Discourse Relation Classification Through the Lens of Cognitive Dimensions: An Empirical Investigation

Yingxue Fu

Existing discourse formalisms use different taxonomies of discourse relations, which require expert knowledge to understand, posing a challenge for annotation and automatic classif…

cs.CL2022

Towards Unification of Discourse Annotation Frameworks

Yingxue Fu

Discourse information is difficult to represent and annotate. Among the major frameworks for annotating discourse information, RST, PDTB and SDRT are widely discussed and used, eac…

cs.CL2021★ 1 cited

Automatic Classification of Human Translation and Machine Translation: A Study from the Perspective of Lexical Diversity

Yingxue Fu, Mark-Jan Nederhof

By using a trigram model and fine-tuning a pretrained BERT model for sequence classification, we show that machine translation and human translation can be classified with an accur…

cs.CL2020★ 2 cited

A Pattern-mining Driven Study on Differences of Newspapers in Expressing Temporal Information

Yingxue Fu, Elaine Ui Dhonnchadha

This paper studies the differences between different types of newspapers in expressing temporal information, which is a topic that has not received much attention. Techniques from…