7 citations · 20 across the 6 of their papers we have counts for
6 papers
Coarse-to-Fine Contrastive Learning on Graphs
Peiyao Zhao, Yuangang Pan, Xin Li +3
Inspired by the impressive success of contrastive learning (CL), a variety of graph augmentation strategies have been employed to learn node representations in a self-supervised ma…
MNER-QG: An End-to-End MRC framework for Multimodal Named Entity Recognition with Query Grounding
Meihuizi Jia, Lei Shen, Xin Shen +5
Multimodal named entity recognition (MNER) is a critical step in information extraction, which aims to detect entity spans and classify them to corresponding entity types given a s…
To be Closer: Learning to Link up Aspects with Opinions
Yuxiang Zhou, Lejian Liao, Yang Gao +2
Dependency parse trees are helpful for discovering the opinion words in aspect-based sentiment analysis (ABSA). However, the trees obtained from off-the-shelf dependency parsers ar…
KVL-BERT: Knowledge Enhanced Visual-and-Linguistic BERT for Visual Commonsense Reasoning
Dandan Song, Siyi Ma, Zhanchen Sun +2
Reasoning is a critical ability towards complete visual understanding. To develop machine with cognition-level visual understanding and reasoning abilities, the visual commonsense…
Earlier Attention? Aspect-Aware LSTM for Aspect-Based Sentiment Analysis
Bowen Xing, Lejian Liao, Dandan Song +4
Aspect-based sentiment analysis (ABSA) aims to predict fine-grained sentiments of comments with respect to given aspect terms or categories. In previous ABSA methods, the importanc…
Personalized Next Point-of-Interest Recommendation via Latent Behavior Patterns Inference
Jing He, Xin Li, Lejian Liao +1
In this paper, we address the problem of personalized next Point-of-interest (POI) recommendation which has become an important and very challenging task for location-based social…