activity
20192022
most citedA Dependency Syntactic Knowledge Augmented Interactive Architecture for End-to-End Aspect-based Sentiment Analysis

8 citations · 8 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2022

BJTU-WeChat's Systems for the WMT22 Chat Translation Task

Yunlong Liang, Fandong Meng, Jinan Xu +2

This paper introduces the joint submission of the Beijing Jiaotong University and WeChat AI to the WMT'22 chat translation task for English-German. Based on the Transformer, we app…

cs.CL2022

Scheduled Multi-task Learning for Neural Chat Translation

Yunlong Liang, Fandong Meng, Jinan Xu +2

Neural Chat Translation (NCT) aims to translate conversational text into different languages. Existing methods mainly focus on modeling the bilingual dialogue characteristics (e.g.…

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.CL2022

MSCTD: A Multimodal Sentiment Chat Translation Dataset

Yunlong Liang, Fandong Meng, Jinan Xu +2

Multimodal machine translation and textual chat translation have received considerable attention in recent years. Although the conversation in its natural form is usually multimoda…

cs.CL2021

Towards Making the Most of Dialogue Characteristics for Neural Chat Translation

Yunlong Liang, Chulun Zhou, Fandong Meng +4

Neural Chat Translation (NCT) aims to translate conversational text between speakers of different languages. Despite the promising performance of sentence-level and context-aware n…

cs.CL2021

Modeling Bilingual Conversational Characteristics for Neural Chat Translation

Yunlong Liang, Fandong Meng, Yufeng Chen +2

Neural chat translation aims to translate bilingual conversational text, which has a broad application in international exchanges and cooperation. Despite the impressive performanc…