most citedMask Attention Networks: Rethinking and Strengthen Transformer

7 citations · 17 across the 11 of their papers we have counts for

collaborators

13 papers

cs.CV20211 cited

Negative Sample is Negative in Its Own Way: Tailoring Negative Sentences for Image-Text Retrieval

Zhihao Fan, Zhongyu Wei, Zejun Li +2

Matching model is essential for Image-Text Retrieval framework. Existing research usually train the model with a triplet loss and explore various strategy to retrieve hard negative…

cs.CL20211 cited

Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training

Zhengyan Li, Yicheng Zou, Chong Zhang +2

Aspect-based sentiment analysis aims to identify the sentiment polarity of a specific aspect in product reviews. We notice that about 30% of reviews do not contain obvious opinion…

cs.IR2021

SAM: A Self-adaptive Attention Module for Context-Aware Recommendation System

Jiabin Liu, Zheng Wei, Zhengpin Li +4

Recently, textual information has been proved to play a positive role in recommendation systems. However, most of the existing methods only focus on representation learning of text…

cs.CV20211 cited

Constructing Phrase-level Semantic Labels to Form Multi-Grained Supervision for Image-Text Retrieval

Zhihao Fan, Zhongyu Wei, Zejun Li +4

Existing research for image text retrieval mainly relies on sentence-level supervision to distinguish matched and mismatched sentences for a query image. However, semantic mismatch…

cs.CL2021

Fine-Grained Element Identification in Complaint Text of Internet Fraud

Tong Liu, Siyuan Wang, Jingchao Fu +7

Existing system dealing with online complaint provides a final decision without explanations. We propose to analyse the complaint text of internet fraud in a fine-grained manner. C…

cs.CL2021

A Partition Filter Network for Joint Entity and Relation Extraction

Zhiheng Yan, Chong Zhang, Jinlan Fu +2

In joint entity and relation extraction, existing work either sequentially encode task-specific features, leading to an imbalance in inter-task feature interaction where features e…