MODE-LSTM: A Parameter-efficient Recurrent Network with Multi-Scale for Sentence Classification

no code implementations • EMNLP 2020 • Qianli Ma, Zhenxi Lin, Jiangyue Yan, Zipeng Chen, Liuhong Yu

The central problem of sentence classification is to extract multi-scale n-gram features for understanding the semantic meaning of sentences.

General Classification Sentence +1

CATE: A Contrastive Pre-trained Model for Metaphor Detection with Semi-supervised Learning

no code implementations • EMNLP 2021 • Zhenxi Lin, Qianli Ma, Jiangyue Yan, Jieyu Chen

Metaphors are ubiquitous in natural language, and detecting them requires contextual reasoning about whether a semantic incongruence actually exists.

A Span-based Dynamic Local Attention Model for Sequential Sentence Classification

no code implementations • ACL 2021 • Xichen Shang, Qianli Ma, Zhenxi Lin, Jiangyue Yan, Zipeng Chen

Sequential sentence classification aims to classify each sentence in the document based on the context in which sentences appear.

Classification Sentence +1

Hierarchy-aware Label Semantics Matching Network for Hierarchical Text Classification

1 code implementation • ACL 2021 • Haibin Chen, Qianli Ma, Zhenxi Lin, Jiangyue Yan

We then introduce a joint embedding loss and a matching learning loss to model the matching relationship between the text semantics and the label semantics.

text-classification Text Classification