activity
20182022
most citedSemantic Neural Machine Translation using AMR

83 citations · 225 across the 27 of their papers we have counts for

collaborators

34 papers

cs.CL20221 cited

Towards Better Document-level Relation Extraction via Iterative Inference

Liang Zhang, Jinsong Su, Yidong Chen +4

Document-level relation extraction (RE) aims to extract the relations between entities from the input document that usually containing many difficultly-predicted entity pairs whose…

cs.CL2022

Getting the Most out of Simile Recognition

Xiaoyue Wang, Linfeng Song, Xin Liu +2

Simile recognition involves two subtasks: simile sentence classification that discriminates whether a sentence contains simile, and simile component extraction that locates the cor…

cs.CL2022

Sentiment-Aware Word and Sentence Level Pre-training for Sentiment Analysis

Shuai Fan, Chen Lin, Haonan Li +6

Most existing pre-trained language representation models (PLMs) are sub-optimal in sentiment analysis tasks, as they capture the sentiment information from word-level while under-c…

cs.CL20221 cited

Towards Robust k-Nearest-Neighbor Machine Translation

Hui Jiang, Ziyao Lu, Fandong Meng +4

k-Nearest-Neighbor Machine Translation (kNN-MT) becomes an important research direction of NMT in recent years. Its main idea is to retrieve useful key-value pairs from an addition…

cs.CL2022

A Variational Hierarchical Model for Neural Cross-Lingual Summarization

Yunlong Liang, Fandong Meng, Chulun Zhou +4

The goal of the cross-lingual summarization (CLS) is to convert a document in one language (e.g., English) to a summary in another one (e.g., Chinese). Essentially, the CLS task is…

cs.CL20221 cited

Type-Driven Multi-Turn Corrections for Grammatical Error Correction

Shaopeng Lai, Qingyu Zhou, Jiali Zeng +4

Grammatical Error Correction (GEC) aims to automatically detect and correct grammatical errors. In this aspect, dominant models are trained by one-iteration learning while performi…