Command Palette
Search for a command to run...
Aspect Oriented Opinion Extraction On Semeval
Metrics
Laptop 2014 (F1)
Restaurant 2014 (F1)
Restaurant 2015 (F1)
Restaurant 2016 (F1)
Results
Performance results of various models on this benchmark
| Paper Title | Repository | |||||
|---|---|---|---|---|---|---|
| BARTABSA | 80.55 | 85.38 | 80.52 | 87.92 | A Unified Generative Framework for Aspect-Based Sentiment Analysis | |
| Dual-MRC | 79.90 | 83.73 | 74.50 | 83.33 | A Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysis | - |
| ONG | 75.77 | 82.33 | 78.81 | 86.01 | Introducing Syntactic Structures into Target Opinion Word Extraction with Deep Learning | - |
| LOTN | 72.02 | 82.21 | 73.29 | 83.62 | Latent Opinions Transfer Network for Target-Oriented Opinion Words Extraction | |
| IOG | 71.35 | 80.02 | 73.25 | 81.69 | Target-oriented Opinion Words Extraction with Target-fused Neural Sequence Labeling | - |
0 of 5 row(s) selected.