Topic Classification on DBPedia
99.1AccuracyFADS-ICL
Evaluation Results
| Method | Links | |
|---|---|---|
| FADS-ICLBackbone=Llama-2 7B, Shots=128-shots2024.05 | 99.1 | |
| kNN-promptingBackbone=Llama-1 13B, Shots=128-shots2024.05 | 99.1 | |
| kNN-promptingBackbone=Llama-1 7B, Shots=128-shots2024.05 | 99 | |
| kNN-promptingBackbone=Llama-2 7B, Shots=128-shots2024.05 | 99 | |
| FADS-ICLBackbone=Llama-1 13B, Shots=128-shots2024.05 | 99 | |
| FADS-ICLBackbone=Llama-1 7B, Shots=128-shots2024.05 | 98.9 | |
| FADS-ICLBackbone=Llama-1 30B, Shots=128-shots2024.05 | 98.9 | |
| FADS-ICLBackbone=Llama-2 70B, Shots=128-shots2024.05 | 98.9 | |
| kNN-promptingBackbone=Llama-2 13B, Shots=128-shots2024.05 | 98.8 | |
| FADS-ICLBackbone=Llama-2 13B, Shots=128-shots2024.05 | 98.8 | |
| kNN-promptingBackbone=Llama-1 30B, Shots=128-shots2024.05 | 98.8 | |
| kNN-promptingBackbone=Llama-2 70B, Shots=128-shots2024.05 | 98.8 | |
| FADS-ICLcandidate pool size (m)=2562024.05 | 98.7 | |
| FADS-ICLNumber of training shots (m)=128, LLM scale=1.5B2024.05 | 98.6 | |
| FADS-ICLBackbone=GPT-2 1.5B, Shots=128-shots2024.05 | 98.6 | |
| FADS-ICLcandidate pool size (m)=1282024.05 | 98.6 | |
| kNN-promptBackbone=Llama-2 7B, Shots=128-shots2024.05 | 98.3 | |
| FADS-ICLNumber of training shots (m)=64, LLM scale=1.5B2024.05 | 98.1 | |
| FADS-ICLcandidate pool size (m)=642024.05 | 98.1 | |
| FADS-ICLcandidate pool size (m)=322024.05 | 97.9 | |
| FADS-ICLBackbone=GPT-2 0.8B, Shots=128-shots2024.05 | 97.7 | |
| ICLModel=LLaMA-3.1-8B2026.05 | 97.68 | |
| kNN-promptBackbone=Llama-2 13B, Shots=128-shots2024.05 | 97.3 | |
| FADS-ICLNumber of training shots (m)=16, LLM scale=1.5B2024.05 | 97.2 | |
| ICLModel=LLaMA-2-13B2026.05 | 96.88 | |
| kNN-promptingNumber of training shots (m)=128, LLM scale=1.5B2024.05 | 96.8 | |
| kNN-promptingBackbone=GPT-2 1.5B, Shots=128-shots2024.05 | 96.8 | |
| GPT Large FTBackbone=GPT Large, Shots=N/A (Fine-tuned)2024.05 | 96.5 | |
| ICLBackbone=Llama-2 7B, Shots=128-shots2024.05 | 95.7 | |
| kNN-promptingBackbone=GPT-2 0.8B, Shots=128-shots2024.05 | 95.5 | |
| FADS-ICLNumber of training shots (m)=8, LLM scale=1.5B2024.05 | 95.3 | |
| kNN-promptingNumber of training shots (m)=64, LLM scale=1.5B2024.05 | 95.2 | |
| BERT Large FTBackbone=BERT Large, Shots=N/A (Fine-tuned)2024.05 | 95.1 | |
| kNN-promptBackbone=Llama-1 13B, Shots=128-shots2024.05 | 95.1 | |
| kNN-promptBackbone=Llama-1 30B, Shots=128-shots2024.05 | 95.1 | |
| DecTn (Shots)=162022.12 | 94.6 | |
| ICLBackbone=Llama-2 70B, Shots=128-shots2024.05 | 94.1 | |
| ICLBackbone=Llama-1 13B, Shots=128-shots2024.05 | 93.8 | |
| kNN-promptingNumber of training shots (m)=16, LLM scale=1.5B2024.05 | 93.5 | |
| LTVModel=LLaMA-3.1-8B2026.05 | 93.36 | |
| ICLBackbone=Llama-1 7B, Shots=128-shots2024.05 | 93.3 | |
| LTVModel=LLaMA-2-13B2026.05 | 93.2 | |
| SubclusteringAnnotation budget (|L|)=1002024.06 | 92.32 | |
| kNN-promptBackbone=Llama-1 7B, Shots=128-shots2024.05 | 91.6 | |
| ICLBackbone=Llama-1 30B, Shots=128-shots2024.05 | 91.2 | |
| kNN-promptingNumber of training shots (m)=8, LLM scale=1.5B2024.05 | 89.9 | |
| Trans-Encodercandidate pool size (m)=2562024.05 | 89.9 | |
| kNN-promptBackbone=Llama-2 70B, Shots=128-shots2024.05 | 89.5 | |
| State VectorModel=LLaMA-2-13B2026.05 | 89.48 | |
| SimCSEcandidate pool size (m)=2562024.05 | 89.1 | |
| SubclusteringAnnotation budget (|L|)=182024.06 | 89.06 | |
| FastGASModel=OPT-6.7B, Annotation Budget=182024.06 | 88.93 | |
| SBERTcandidate pool size (m)=2562024.05 | 88.5 | |
| BM25candidate pool size (m)=2562024.05 | 88.2 | |
| Vote-kModel=OPT-6.7B, Annotation Budget=182024.06 | 88.02 | |
| SBERTcandidate pool size (m)=1282024.05 | 87.2 | |
| SimCSEcandidate pool size (m)=1282024.05 | 87 | |
| Trans-Encodercandidate pool size (m)=1282024.05 | 87 | |
| kNN-promptNumber of training shots (m)=64, LLM scale=1.5B2024.05 | 86.4 | |
| kNN-promptNumber of training shots (m)=128, LLM scale=1.5B2024.05 | 86.4 | |
| kNN-promptBackbone=GPT-2 1.5B, Shots=128-shots2024.05 | 86.4 | |
| kNN-promptNumber of training shots (m)=16, LLM scale=1.5B2024.05 | 85.8 | |
| kNN-promptNumber of training shots (m)=32, LLM scale=1.5B2024.05 | 85.7 | |
| Trans-Encodercandidate pool size (m)=642024.05 | 85.6 | |
| BM25candidate pool size (m)=1282024.05 | 85.5 | |
| kNN-promptNumber of training shots (m)=4, LLM scale=1.5B2024.05 | 85.2 | |
| MUPPET2022.12 | 85.17 | |
| kNN-promptNumber of training shots (m)=8, LLM scale=1.5B2024.05 | 84.9 | |
| SimCSEcandidate pool size (m)=642024.05 | 84.8 | |
| SBERTcandidate pool size (m)=642024.05 | 84.6 | |
| SBERTcandidate pool size (m)=322024.05 | 83.8 | |
| In-Context Learning2024.05 | 83.5 | |
| BM25candidate pool size (m)=642024.05 | 83.4 | |
| Task VectorModel=LLaMA-3.1-8B2026.05 | 83.24 | |
| IDEALModel=OPT-6.7B, Annotation Budget=182024.06 | 83.2 | |
| Trans-Encodercandidate pool size (m)=322024.05 | 82.8 | |
| SimCSEcandidate pool size (m)=322024.05 | 82.3 | |
| ICLNumber of training shots (m)=4, LLM scale=1.5B2024.05 | 82 | |
| ICLNumber of training shots (m)=8, LLM scale=1.5B2024.05 | 82 | |
| ICLNumber of training shots (m)=16, LLM scale=1.5B2024.05 | 82 | |
| ICLNumber of training shots (m)=32, LLM scale=1.5B2024.05 | 82 | |
| ICLNumber of training shots (m)=64, LLM scale=1.5B2024.05 | 82 | |
| ICLNumber of training shots (m)=128, LLM scale=1.5B2024.05 | 82 | |
| ICLBackbone=GPT-2 1.5B, Shots=128-shots2024.05 | 82 | |
| ICLBackbone=Llama-2 13B, Shots=128-shots2024.05 | 81.5 | |
| FastGASModel=GPT-Neo-2.7B, Annotation Budget=182024.06 | 80.86 | |
| State VectorModel=LLaMA-3.1-8B2026.05 | 80.8 | |
| Vote-kModel=GPT-Neo-2.7B, Annotation Budget=182024.06 | 80.73 | |
| Task VectorModel=LLaMA-2-13B2026.05 | 80.72 | |
| BM25candidate pool size (m)=322024.05 | 80.7 | |
| FADS-ICLNumber of training shots (m)=32, LLM scale=1.5B2024.05 | 79.9 | |
| kNN-promptingNumber of training shots (m)=4, LLM scale=1.5B2024.05 | 79.1 | |
| I2CLModel=LLaMA-2-13B2026.05 | 79 | |
| IDEALModel=GPT-Neo-2.7B, Annotation Budget=182024.06 | 78.38 | |
| ColD-Fusion2022.12 | 78.15 | |
| Multitask2022.12 | 77.69 | |
| Finetune2022.12 | 77.49 | |
| Function VectorModel=LLaMA-2-13B2026.05 | 76.4 | |
| Zero-shotModel=LLaMA-2-13B2026.05 | 76.2 | |
| Latent Concept LearningLLM=GPT3-d (175B)2023.01 | 75.5 |