3 citations · 3 across the 5 of their papers we have counts for
5 papers
Hierarchical Aligned Multimodal Learning for NER on Tweet Posts
Peipei Liu, Hong Li, Yimo Ren +4
Mining structured knowledge from tweets using named entity recognition (NER) can be beneficial for many down stream applications such as recommendation and intention understanding.…
Multi-Granularity Cross-Modality Representation Learning for Named Entity Recognition on Social Media
Peipei Liu, Gaosheng Wang, Hong Li +4
Named Entity Recognition (NER) on social media refers to discovering and classifying entities from unstructured free-form content, and it plays an important role for various applic…
CEntRE: A paragraph-level Chinese dataset for Relation Extraction among Enterprises
Peipei Liu, Hong Li, Zhiyu Wang +5
Enterprise relation extraction aims to detect pairs of enterprise entities and identify the business relations between them from unstructured or semi-structured text data, and it i…
Improving the Modality Representation with Multi-View Contrastive Learning for Multimodal Sentiment Analysis
Peipei Liu, Xin Zheng, Hong Li +4
Modality representation learning is an important problem for multimodal sentiment analysis (MSA), since the highly distinguishable representations can contribute to improving the a…
Multi-features based Semantic Augmentation Networks for Named Entity Recognition in Threat Intelligence
Peipei Liu, Hong Li, Zuoguang Wang +3
Extracting cybersecurity entities such as attackers and vulnerabilities from unstructured network texts is an important part of security analysis. However, the sparsity of intellig…