activity
20182022
most citedDialogue-Based Relation Extraction

6 citations · 20 across the 9 of their papers we have counts for

collaborators

11 papers

cs.CL2021

Connect-the-Dots: Bridging Semantics between Words and Definitions via Aligning Word Sense Inventories

Wenlin Yao, Xiaoman Pan, Lifeng Jin +3

Word Sense Disambiguation (WSD) aims to automatically identify the exact meaning of one word according to its context. Existing supervised models struggle to make correct predictio…

cs.CL2021

Self-Teaching Machines to Read and Comprehend with Large-Scale Multi-Subject Question-Answering Data

Dian Yu, Kai Sun, Dong Yu +1

In spite of much recent research in the area, it is still unclear whether subject-area question-answering data is useful for machine reading comprehension (MRC) tasks. In this pape…

cs.CL20204 cited

Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension

Hongyu Gong, Yelong Shen, Dian Yu +2

In this paper, we study machine reading comprehension (MRC) on long texts, where a model takes as inputs a lengthy document and a question and then extracts a text span from the do…

cs.CL20206 cited

Dialogue-Based Relation Extraction

Dian Yu, Kai Sun, Claire Cardie +1

We present the first human-annotated dialogue-based relation extraction (RE) dataset DialogRE, aiming to support the prediction of relation(s) between two arguments that appear in…

cs.CL2020

CLUE: A Chinese Language Understanding Evaluation Benchmark

Liang Xu, Hai Hu, Xuanwei Zhang +29

The advent of natural language understanding (NLU) benchmarks for English, such as GLUE and SuperGLUE allows new NLU models to be evaluated across a diverse set of tasks. These com…

cs.CL20194 cited

Improving Pre-Trained Multilingual Models with Vocabulary Expansion

Hai Wang, Dian Yu, Kai Sun +2

Recently, pre-trained language models have achieved remarkable success in a broad range of natural language processing tasks. However, in multilingual setting, it is extremely reso…