Multi-Domain Sentiment Classification

1 papers with code • 1 benchmarks • 1 datasets

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Datasets


Latest papers with no code

Learn2Weight: Parameter Adaptation against Similar-domain Adversarial Attacks

no code yet • COLING 2022

Recent work in black-box adversarial attacks for NLP systems has attracted much attention.

Learning to Share by Masking the Non-shared for Multi-domain Sentiment Classification

no code yet • 17 Apr 2021

To this end, we propose the BertMasker network which explicitly masks domain-related words from texts, learns domain-invariant sentiment features from these domain-agnostic texts, and uses those masked words to form domain-aware sentence representations.

Learn2Weight: Weights Transfer Defense against Similar-domain Adversarial Attacks

no code yet • 1 Jan 2021

Recent work in black-box adversarial attacks for NLP systems has attracted attention.

Dual Adversarial Co-Learning for Multi-Domain Text Classification

no code yet • 18 Sep 2019

In this paper we propose a novel dual adversarial co-learning approach for multi-domain text classification (MDTC).

Learning Domain Representation for Multi-Domain Sentiment Classification

no code yet • NAACL 2018

It is useful to leveraging data available for all existing domains to enhance performance on different domains.