activity
20182021
most citedStructure-Level Knowledge Distillation For Multilingual Sequence Labeling

3 citations · 5 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL2021

MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations

Xinyin Ma, Yong Jiang, Nguyen Bach +4

Entity retrieval, which aims at disambiguating mentions to canonical entities from massive KBs, is essential for many tasks in natural language processing. Recent progress in entit…

cs.CL2020

An Investigation of Potential Function Designs for Neural CRF

Zechuan Hu, Yong Jiang, Nguyen Bach +4

The neural linear-chain CRF model is one of the most widely-used approach to sequence labeling. In this paper, we investigate a series of increasingly expressive potential function…

astro-ph.IM20202 cited

Detection of asteroid trails in Hubble Space Telescope images using Deep Learning

Andrei A. Parfeni, Laurentiu I. Caramete, Andreea M. Dobre +1

We present an application of Deep Learning for the image recognition of asteroid trails in single-exposure photos taken by the Hubble Space Telescope. Using algorithms based on mul…

cs.CL2020

AIN: Fast and Accurate Sequence Labeling with Approximate Inference Network

Xinyu Wang, Yong Jiang, Nguyen Bach +4

The linear-chain Conditional Random Field (CRF) model is one of the most widely-used neural sequence labeling approaches. Exact probabilistic inference algorithms such as the forwa…

cs.CL20203 cited

Structure-Level Knowledge Distillation For Multilingual Sequence Labeling

Xinyu Wang, Yong Jiang, Nguyen Bach +3

Multilingual sequence labeling is a task of predicting label sequences using a single unified model for multiple languages. Compared with relying on multiple monolingual models, us…

cs.CV2018

Unsupervised Multi-modal Neural Machine Translation

Yuanhang Su, Kai Fan, Nguyen Bach +2

Unsupervised neural machine translation (UNMT) has recently achieved remarkable results with only large monolingual corpora in each language. However, the uncertainty of associatin…