Sentiment Analysis On Semeval 2014 Task 4

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이 벤치마크에서 각 모델의 성능 결과

모델 이름	F1	Paper Title
BERT-E2E-ABSA	61.12	Exploiting BERT for End-to-End Aspect-based Sentiment Analysis
GRACE	70.71	GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysis
DOER	60.35	DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
SPAN	68.06	Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classification
InstructABSA	79.34	InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis
IMN	58.37	An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis
E2E-TBSA	57.9	A Unified Model for Opinion Target Extraction and Target Sentiment Prediction
RACL-BERT	63.4	Relation-Aware Collaborative Learning for Unified Aspect-Based Sentiment Analysis

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