Aspect Sentiment Classification on Rest
71.76F1 ScoreBM25 + Feedback-ICL
Evaluation results
| Method | Links | |
|---|---|---|
| BM25 + Feedback-ICLBackbone=Llama-2 13B Chat, Evaluation Protocol=In-context learning, Number of in-context examples=4, Retrieval Strategy=BM252024.06 | 71.76 | |
| SBERT + Feedback-ICLBackbone=Llama-2 13B Chat, Evaluation Protocol=In-context learning, Number of in-context examples=4, Retrieval Strategy=SBERT2024.06 | 71.29 | |
| Random + Feedback-ICLBackbone=Llama-2 13B Chat, Evaluation Protocol=In-context learning, Number of in-context examples=4, Retrieval Strategy=Random2024.06 | 71.16 | |
| K-Means + Feedback-ICLBackbone=Llama-2 13B Chat, Evaluation Protocol=In-context learning, Number of in-context examples=4, Retrieval Strategy=K-Means2024.06 | 71.1 | |
| K-MeansBackbone=Llama-2 13B Chat, Evaluation Protocol=In-context learning, Number of in-context examples=4, Retrieval Strategy=K-Means2024.06 | 71.01 | |
| MMR + Feedback-ICLBackbone=Llama-2 13B Chat, Evaluation Protocol=In-context learning, Number of in-context examples=4, Retrieval Strategy=MMR2024.06 | 69.76 | |
| BM25Backbone=Llama-2 13B Chat, Evaluation Protocol=In-context learning, Number of in-context examples=4, Retrieval Strategy=BM252024.06 | 68.99 | |
| RandomBackbone=Llama-2 13B Chat, Evaluation Protocol=In-context learning, Number of in-context examples=4, Retrieval Strategy=Random2024.06 | 68.77 | |
| MMRBackbone=Llama-2 13B Chat, Evaluation Protocol=In-context learning, Number of in-context examples=4, Retrieval Strategy=MMR2024.06 | 68.3 | |
| SBERTBackbone=Llama-2 13B Chat, Evaluation Protocol=In-context learning, Number of in-context examples=4, Retrieval Strategy=SBERT2024.06 | 68.21 | |
| BERT-FTBackbone=BERT-base, Evaluation Protocol=Fine-tuning2024.06 | 64.59 |