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Found 4 papers, 2 papers with code
E2S2: Encoding-Enhanced Sequence-to-Sequence Pretraining for Language Understanding and Generation
Sequence-to-sequence (seq2seq) learning has become a popular trend for pretraining language models, due to its succinct and universal framework.
A Contrastive Cross-Channel Data Augmentation Framework for Aspect-based Sentiment Analysis
To mitigate this issue, we design a novel training framework, called Contrastive Cross-Channel Data Augmentation (C3DA).
Knowledge Graph Augmented Network Towards Multiview Representation Learning for Aspect-based Sentiment Analysis
To this end, we propose a knowledge graph augmented network (KGAN), which aims to effectively incorporate external knowledge with explicitly syntactic and contextual information.
Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment Analysis
In practice, we formulate the model pretrained on the sampled instances into a knowledge guidance model and a learner model, respectively.
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