BERT-E2E-ABSA

Reported on 4 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing5 results

Sentiment AnalysisonSemEval 2014 Task 4 Subtask 1+2
F1· 2019-10-02
61.12
best: 83.76 (gpt-3.5 finetuned)
Exploiting BERT for End-to-End Aspect-based Sentiment Analysis arXiv:1910.00883
Sentiment AnalysisonSemEval 2014 Task 4 Subtask 1+2
F1· 2019-10-02
61.12
best: 83.76 (gpt-3.5 finetuned)
Exploiting BERT for End-to-End Aspect-based Sentiment Analysis arXiv:1910.00883
Sentiment AnalysisonSemEval 2014 Task 4 Laptop
F1· 2019-10-02
61.12
best: 79.34 (InstructABSA)
Exploiting BERT for End-to-End Aspect-based Sentiment Analysis arXiv:1910.00883
Aspect-Based Sentiment Analysis (ABSA)onSemEval 2014 Task 4 Subtask 1+2
F1· 2019-10-02
61.12
best: 83.76 (gpt-3.5 finetuned)
Exploiting BERT for End-to-End Aspect-based Sentiment Analysis arXiv:1910.00883
Aspect-Based Sentiment Analysis (ABSA)onSemEval 2014 Task 4 Laptop
F1· 2019-10-02
61.12
best: 79.34 (InstructABSA)
Exploiting BERT for End-to-End Aspect-based Sentiment Analysis arXiv:1910.00883