activity
20182022
most citedAnonymized BERT: An Augmentation Approach to the Gendered Pronoun Resolution Challenge

1 citations · 2 across the 3 of their papers we have counts for

collaborators

6 papers

cs.IR2022

Modeling User Behavior with Graph Convolution for Personalized Product Search

Fan Lu, Qimai Li, Bo Liu +7

User preference modeling is a vital yet challenging problem in personalized product search. In recent years, latent space based methods have achieved state-of-the-art performance b…

cs.CV20211 cited

Google Landmark Retrieval 2021 Competition Third Place Solution

Qishen Ha, Bo Liu, Hongwei Zhang

We present our solutions to the Google Landmark Challenges 2021, for both the retrieval and the recognition tracks. Both solutions are ensembles of transformers and ConvNet models…

cs.CV2020

Identifying Melanoma Images using EfficientNet Ensemble: Winning Solution to the SIIM-ISIC Melanoma Classification Challenge

Qishen Ha, Bo Liu, Fuxu Liu

We present our winning solution to the SIIM-ISIC Melanoma Classification Challenge. It is an ensemble of convolutions neural network (CNN) models with different backbones and input…

cs.CV2020

Google Landmark Recognition 2020 Competition Third Place Solution

Qishen Ha, Bo Liu, Fuxu Liu +1

We present our third place solution to the Google Landmark Recognition 2020 competition. It is an ensemble of global features only Sub-center ArcFace models. We introduce dynamic m…

cs.CL20191 cited

Anonymized BERT: An Augmentation Approach to the Gendered Pronoun Resolution Challenge

Bo Liu

We present our 7th place solution to the Gendered Pronoun Resolution challenge, which uses BERT without fine-tuning and a novel augmentation strategy designed for contextual embedd…

cs.CV2018

Constrained-size Tensorflow Models for YouTube-8M Video Understanding Challenge

Tianqi Liu, Bo Liu

This paper presents our 7th place solution to the second YouTube-8M video understanding competition which challenges participates to build a constrained-size model to classify mill…