Deep learning for aspect-based sentiment analysis: a review
L Zhu, M Xu, Y Bao, Y Xu, X Kong - PeerJ Computer Science, 2022 - peerj.com
User-generated content on various Internet platforms is growing explosively, and contains
valuable information that helps decision-making. However, extracting this information …
valuable information that helps decision-making. However, extracting this information …
KT-GAN: Knowledge-transfer generative adversarial network for text-to-image synthesis
This paper presents a new framework, Knowledge-Transfer Generative Adversarial Network
(KT-GAN), for fine-grained text-to-image generation. We introduce two novel mechanisms …
(KT-GAN), for fine-grained text-to-image generation. We introduce two novel mechanisms …
Improving aspect-based sentiment analysis with gated graph convolutional networks and syntax-based regulation
Aspect-based Sentiment Analysis (ABSA) seeks to predict the sentiment polarity of a
sentence toward a specific aspect. Recently, it has been shown that dependency trees can …
sentence toward a specific aspect. Recently, it has been shown that dependency trees can …
EATN: An efficient adaptive transfer network for aspect-level sentiment analysis
Aspect-level sentiment analysis is a granular emotional classification task that refers to
identifying sentiment polarities towards aspects in a sentence. Although previous research …
identifying sentiment polarities towards aspects in a sentence. Although previous research …
Meta-prompt based learning for low-resource false information detection
The wide spread of false information has detrimental effects on society, and false information
detection has received wide attention. When new domains appear, the relevant labeled data …
detection has received wide attention. When new domains appear, the relevant labeled data …
Meta-KD: A meta knowledge distillation framework for language model compression across domains
Pre-trained language models have been applied to various NLP tasks with considerable
performance gains. However, the large model sizes, together with the long inference time …
performance gains. However, the large model sizes, together with the long inference time …
Reproducibility, replicability and beyond: Assessing production readiness of aspect based sentiment analysis in the wild
With the exponential growth of online marketplaces and user-generated content therein,
aspect-based sentiment analysis has become more important than ever. In this work, we …
aspect-based sentiment analysis has become more important than ever. In this work, we …
Unsupervised domain adaptation for hate speech detection using a data augmentation approach
Online harassment in the form of hate speech has been on the rise in recent years.
Addressing the issue requires a combination of content moderation by people, aided by …
Addressing the issue requires a combination of content moderation by people, aided by …
Meta fine-tuning neural language models for multi-domain text mining
Pre-trained neural language models bring significant improvement for various NLP tasks, by
fine-tuning the models on task-specific training sets. During fine-tuning, the parameters are …
fine-tuning the models on task-specific training sets. During fine-tuning, the parameters are …
Wider & closer: Mixture of short-channel distillers for zero-shot cross-lingual named entity recognition
Zero-shot cross-lingual named entity recognition (NER) aims at transferring knowledge from
annotated and rich-resource data in source languages to unlabeled and lean-resource data …
annotated and rich-resource data in source languages to unlabeled and lean-resource data …