activity
20192021
most citedGRN: Gated Relation Network to Enhance Convolutional Neural Network for Named Entity Recognition

10 citations · 10 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2021

An Exploratory Study on Long Dialogue Summarization: What Works and What's Next

Yusen Zhang, Ansong Ni, Tao Yu +6

Dialogue summarization helps readers capture salient information from long conversations in meetings, interviews, and TV series. However, real-world dialogues pose a great challeng…

cs.CL2021

SummerTime: Text Summarization Toolkit for Non-experts

Ansong Ni, Zhangir Azerbayev, Mutethia Mutuma +5

Recent advances in summarization provide models that can generate summaries of higher quality. Such models now exist for a number of summarization tasks, including query-based summ…

cs.CL2021

Logic-Consistency Text Generation from Semantic Parses

Chang Shu, Yusen Zhang, Xiangyu Dong +3

Text generation from semantic parses is to generate textual descriptions for formal representation inputs such as logic forms and SQL queries. This is challenging due to two reason…

cs.CL2020

Did You Ask a Good Question? A Cross-Domain Question Intention Classification Benchmark for Text-to-SQL

Yusen Zhang, Xiangyu Dong, Shuaichen Chang +3

Neural models have achieved significant results on the text-to-SQL task, in which most current work assumes all the input questions are legal and generates a SQL query for any inpu…

cs.CL201910 cited

GRN: Gated Relation Network to Enhance Convolutional Neural Network for Named Entity Recognition

Hui Chen, Zijia Lin, Guiguang Ding +3

The dominant approaches for named entity recognition (NER) mostly adopt complex recurrent neural networks (RNN), e.g., long-short-term-memory (LSTM). However, RNNs are limited by t…