activity
20172021
most citedTranslating Pro-Drop Languages with Reconstruction Models

22 citations · 112 across the 20 of their papers we have counts for

collaborators

40 papers

cs.CL20212 cited

Tail-to-Tail Non-Autoregressive Sequence Prediction for Chinese Grammatical Error Correction

Piji Li, Shuming Shi

We investigate the problem of Chinese Grammatical Error Correction (CGEC) and present a new framework named Tail-to-Tail (\textbf{TtT}) non-autoregressive sequence prediction to ad…

cs.CL202020 cited

TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis

Haisong Zhang, Lemao Liu, Haiyun Jiang +14

This technique report introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities. Com…

cs.CL2020

Dialogue Response Selection with Hierarchical Curriculum Learning

Yixuan Su, Deng Cai, Qingyu Zhou +6

We study the learning of a matching model for dialogue response selection. Motivated by the recent finding that models trained with random negative samples are not ideal in real-wo…

cs.CL20207 cited

Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition

Yangming Li, Lemao Liu, Shuming Shi

In many scenarios, named entity recognition (NER) models severely suffer from unlabeled entity problem, where the entities of a sentence may not be fully annotated. Through empiric…

cs.CL2020

Segmenting Natural Language Sentences via Lexical Unit Analysis

Yangming Li, Lemao Liu, Shuming Shi

In this work, we present Lexical Unit Analysis (LUA), a framework for general sequence segmentation tasks. Given a natural language sentence, LUA scores all the valid segmentation…

cs.CL2020

When Hearst Is not Enough: Improving Hypernymy Detection from Corpus with Distributional Models

Changlong Yu, Jialong Han, Peifeng Wang +4

We address hypernymy detection, i.e., whether an is-a relationship exists between words (x, y), with the help of large textual corpora. Most conventional approaches to this task ha…