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Aspect Based Sentiment Analysis Absa On Aste

Metrics

F1 (L14)

F1 (R15)

F1 (R16)

F1(R14)

Results

Performance results of various models on this benchmark

					Paper Title	Repository
MvP (multi-task)	65.30	69.44	73.10	76.30	MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction
ASTE-Transformer	64.90	72.10	76.19	76.06	ASTE Transformer Modelling Dependencies in Aspect-Sentiment Triplet Extraction
Seq2Path	64.82	65.88	72.87	75.52	Seq2Path: Generating Sentiment Tuples as Paths of a Tree	-
MvP	63.33	65.89	73.48	74.05	MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction
UIE	62.94	64.41	72.86	72.55	Unified Structure Generation for Universal Information Extraction
AugABSA	62.66	65.80	74.23	73.76	Generative Data Augmentation for Aspect Sentiment Quad Prediction	-
LEGO-ABSA (multi-task)	62.20	64.40	69.90	73.70	LEGO-ABSA: A Prompt-based Task Assemblable Unified Generative Framework for Multi-task Aspect-based Sentiment Analysis	-
DLO	61.46	64.26	73.03	72.39	Improving Aspect Sentiment Quad Prediction via Template-Order Data Augmentation
Paraphrase	61.13	62.56	71.70	72.03	Aspect Sentiment Quad Prediction as Paraphrase Generation
Span-ASTE	59.38	63.27	70.26	71.85	Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction
GAS	58.19	60.23	69.05	70.52	Towards Generative Aspect-Based Sentiment Analysis	-
ChatGPT (gpt-3.5-turbo, few-shot)	38.12	-	-	-	MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction
ChatGPT (gpt-3.5-turbo, zero-shot)	36.05	-	-	-	MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction

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