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Aspect Sentiment Triplet Extraction
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Aspect Sentiment Triplet Extraction (ASTE) is the task of extracting the triplets of target entities, their associated sentiment, and opinion spans explaining the reason for the sentiment.
논문
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Polish-ASTE: Aspect-Sentiment Triplet Extraction Datasets for Polish
Boundary-Driven Table-Filling with Cross-Granularity Contrastive Learning for Aspect Sentiment Triplet Extraction
Test-Time Code-Switching for Cross-lingual Aspect Sentiment Triplet Extraction
Train Once for All: A Transitional Approach for Efficient Aspect Sentiment Triplet Extraction
ASTE Transformer Modelling Dependencies in Aspect-Sentiment Triplet Extraction
Table-Filling via Mean Teacher for Cross-domain Aspect Sentiment Triplet Extraction
10 Years of Fair Representations: Challenges and Opportunities
Deep Content Understanding Toward Entity and Aspect Target Sentiment Analysis on Foundation Models
MiniConGTS: A Near Ultimate Minimalist Contrastive Grid Tagging Scheme for Aspect Sentiment Triplet Extraction
E2TP: Element to Tuple Prompting Improves Aspect Sentiment Tuple Prediction
Rethinking ASTE: A Minimalist Tagging Scheme Alongside Contrastive Learning
Dual Encoder: Exploiting the Potential of Syntactic and Semantic for Aspect Sentiment Triplet Extraction
Prompt Based Tri-Channel Graph Convolution Neural Network for Aspect Sentiment Triplet Extraction
FOAL: Fine-grained Contrastive Learning for Cross-domain Aspect Sentiment Triplet Extraction
Indo LEGO-ABSA: A Multitask Generative Aspect Based Sentiment Analysis for Indonesian Language
CONTRASTE: Supervised Contrastive Pre-training With Aspect-based Prompts For Aspect Sentiment Triplet Extraction
A semantically enhanced dual encoder for aspect sentiment triplet extraction
A Pairing Enhancement Approach for Aspect Sentiment Triplet Extraction
Measuring Your ASTE Models in The Wild: A Diversified Multi-domain Dataset For Aspect Sentiment Triplet Extraction
Domain-Expanded ASTE: Rethinking Generalization in Aspect Sentiment Triplet Extraction
MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction
A Weak Supervision Approach for Few-Shot Aspect Based Sentiment
A Better Choice: Entire-space Datasets for Aspect Sentiment Triplet Extraction
STAGE: Span Tagging and Greedy Inference Scheme for Aspect Sentiment Triplet Extraction
UnifiedABSA: A Unified ABSA Framework Based on Multi-task Instruction Tuning
Structural Bias for Aspect Sentiment Triplet Extraction
Pretrained Language Encoders are Natural Tagging Frameworks for Aspect Sentiment Triplet Extraction
A Span-level Bidirectional Network for Aspect Sentiment Triplet Extraction
Nonautoregressive Encoder-Decoder Neural Framework for End-to-End Aspect-Based Sentiment Triplet Extraction
Aspect-Sentiment-Multiple-Opinion Triplet Extraction
PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction
Aspect Sentiment Triplet Extraction Using Reinforcement Learning
Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction
Explicit Interaction Network for Aspect Sentiment Triplet Extraction
A Unified Generative Framework for Aspect-Based Sentiment Analysis
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