activity
20142022
most citedStructure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion

213 citations · 773 across the 22 of their papers we have counts for

collaborators

22 papers

cs.CL2022

Learning Semantic Textual Similarity via Topic-informed Discrete Latent Variables

Erxin Yu, Lan Du, Yuan Jin +2

Recently, discrete latent variable models have received a surge of interest in both Natural Language Processing (NLP) and Computer Vision (CV), attributed to their comparable perfo…

cs.IR2022★ 2 cited

A Unified Collaborative Representation Learning for Neural-Network based Recommender Systems

Yuanbo Xu, En Wang, Yongjian Yang +1

Most NN-RSs focus on accuracy by building representations from the direct user-item interactions (e.g., user-item rating matrix), while ignoring the underlying relatedness between…

cs.CL2021

Eliminating Sentiment Bias for Aspect-Level Sentiment Classification with Unsupervised Opinion Extraction

Bo Wang, Tao Shen, Guodong Long +2

Aspect-level sentiment classification (ALSC) aims at identifying the sentiment polarity of a specified aspect in a sentence. ALSC is a practical setting in aspect-based sentiment a…

cs.CL2021★ 43 cited

Using Prior Knowledge to Guide BERT's Attention in Semantic Textual Matching Tasks

Tingyu Xia, Yue Wang, Yuan Tian +1

We study the problem of incorporating prior knowledge into a deep Transformer-based model,i.e.,Bidirectional Encoder Representations from Transformers (BERT), to enhance its perfor…

cs.SI2021★ 4 cited

Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection

Yuxiang Ren, Bo Wang, Jiawei Zhang +1

The explosive growth of fake news along with destructive effects on politics, economy, and public safety has increased the demand for fake news detection. Fake news on social media…

cs.LG2020★ 27 cited

MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler

Zhining Liu, Pengfei Wei, Jing Jiang +3

Imbalanced learning (IL), i.e., learning unbiased models from class-imbalanced data, is a challenging problem. Typical IL methods including resampling and reweighting were designed…