arXiv:2010.12401
공식 코드 · Papers with Code
Pretraining and Fine-Tuning Strategies for Sentiment Analysis of Latvian Tweets
원문 초록
In this paper, we present various pre-training strategies that aid in im-proving the accuracy of the sentiment classification task. We, at first, pre-trainlanguage representation models using these strategies and then fine-tune them onthe downstream task. Experimental results on a time-balanced tweet evaluation setshow the improvement over the previous technique. We achieve 76% accuracy forsentiment analysis on Latvian tweets, which is a substantial improvement over pre-vious work
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A Personalized Conversational Benchmark: Towards Simulating Personalized Conversations
Divide (Text) and Conquer (Sentiment): Improved Sentiment Classification by Constituent Conflict Resolution
Bug Destiny Prediction in Large Open-Source Software Repositories through Sentiment Analysis and BERT Topic Modeling
Breaking BERT: Gradient Attack on Twitter Sentiment Analysis for Targeted Misclassification
ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
On the Applicability of Zero-Shot Cross-Lingual Transfer Learning for Sentiment Classification in Distant Language Pairs
토론
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