activity
20152023
most citedBridging Neural Machine Translation and Bilingual Dictionaries

46 citations · 223 across the 29 of their papers we have counts for

collaborators

36 papers

cs.CL2023★ 3 cited

CFSum: A Coarse-to-Fine Contribution Network for Multimodal Summarization

Min Xiao, Junnan Zhu, Haitao Lin +2

Multimodal summarization usually suffers from the problem that the contribution of the visual modality is unclear. Existing multimodal summarization approaches focus on designing t…

cs.CL2023

Multi-Teacher Knowledge Distillation For Text Image Machine Translation

Cong Ma, Yaping Zhang, Mei Tu +3

Text image machine translation (TIMT) has been widely used in various real-world applications, which translates source language texts in images into another target language sentenc…

cs.CL2023

E2TIMT: Efficient and Effective Modal Adapter for Text Image Machine Translation

Cong Ma, Yaping Zhang, Mei Tu +3

Text image machine translation (TIMT) aims to translate texts embedded in images from one source language to another target language. Existing methods, both two-stage cascade and o…

cs.CL2021

Learning to Select the Next Reasonable Mention for Entity Linking

Jian Sun, Yu Zhou, Chengqing Zong

Entity linking aims to establish a link between entity mentions in a document and the corresponding entities in knowledge graphs (KGs). Previous work has shown the effectiveness of…

cs.CL2021★ 4 cited

CSDS: A Fine-Grained Chinese Dataset for Customer Service Dialogue Summarization

Haitao Lin, Liqun Ma, Junnan Zhu +4

Dialogue summarization has drawn much attention recently. Especially in the customer service domain, agents could use dialogue summaries to help boost their works by quickly knowin…

cs.CL2021★ 2 cited

Augmenting Slot Values and Contexts for Spoken Language Understanding with Pretrained Models

Haitao Lin, Lu Xiang, Yu Zhou +2

Spoken Language Understanding (SLU) is one essential step in building a dialogue system. Due to the expensive cost of obtaining the labeled data, SLU suffers from the data scarcity…