activity
20202023
most citedEntity-to-Text based Data Augmentation for various Named Entity Recognition Tasks

2 citations · 4 across the 7 of their papers we have counts for

collaborators

9 papers

cs.IR2023

Improving Text Matching in E-Commerce Search with A Rationalizable, Intervenable and Fast Entity-Based Relevance Model

Jiong Cai, Yong Jiang, Yue Zhang +10

Discovering the intended items of user queries from a massive repository of items is one of the main goals of an e-commerce search system. Relevance prediction is essential to the…

cs.CL2023

Translate the Beauty in Songs: Jointly Learning to Align Melody and Translate Lyrics

Chengxi Li, Kai Fan, Jiajun Bu +3

Song translation requires both translation of lyrics and alignment of music notes so that the resulting verse can be sung to the accompanying melody, which is a challenging problem…

cs.CL2023

Adapting Offline Speech Translation Models for Streaming with Future-Aware Distillation and Inference

Biao Fu, Minpeng Liao, Kai Fan +4

A popular approach to streaming speech translation is to employ a single offline model with a wait-k policy to support different latency requirements, which is simpler than trainin…

cs.CL2022★ 1 cited

Discrete Cross-Modal Alignment Enables Zero-Shot Speech Translation

Chen Wang, Yuchen Liu, Boxing Chen +4

End-to-end Speech Translation (ST) aims at translating the source language speech into target language text without generating the intermediate transcriptions. However, the trainin…

cs.CL2022★ 2 cited

Entity-to-Text based Data Augmentation for various Named Entity Recognition Tasks

Xuming Hu, Yong Jiang, Aiwei Liu +5

Data augmentation techniques have been used to alleviate the problem of scarce labeled data in various NER tasks (flat, nested, and discontinuous NER tasks). Existing augmentation…

cs.CL2021★ 1 cited

ITA: Image-Text Alignments for Multi-Modal Named Entity Recognition

Xinyu Wang, Min Gui, Yong Jiang +6

Recently, Multi-modal Named Entity Recognition (MNER) has attracted a lot of attention. Most of the work utilizes image information through region-level visual representations obta…