Topic Classification on AG-News
95.58AccuracyTay et al. (2022)
Evaluation Results
| Method | Links | |
|---|---|---|
| Tay et al. (2022)Mode=Fully-supervised, Model Parameters=4x of UD (~44B)2022.11 | 95.58 | |
| UD+-XXLMode=Fully-supervised, Backbone=T5-XXL encoder, Model Parameters=11B2022.11 | 95.56 | |
| Yang et al., 2019#Params (M)=-2026.06 | 95.5 | |
| BERT2026.04 | 94.75 | |
| RLLR_MIXEDBackbone=LLaMA2 7B2024.05 | 93.5 | |
| RLLRBackbone=LLaMA2 7B2024.05 | 93.4 | |
| RLLRBackbone=ChatGLM3 6B2024.05 | 93.4 | |
| RLLR_MIXEDBackbone=ChatGLM3 6B2024.05 | 93.4 | |
| SFTBackbone=Baichuan2 7B2024.05 | 93.4 | |
| SFT w. rat.Backbone=ChatGLM3 6B2024.05 | 93.1 | |
| RLHFBackbone=ChatGLM3 6B2024.05 | 93.1 | |
| RLLRBackbone=Mistral 7B2024.05 | 93.1 | |
| LLM-Guided TM2026.04 | 93.1 | |
| RLHFBackbone=LLaMA2 7B2024.05 | 93 | |
| SFTBackbone=ChatGLM3 6B2024.05 | 93 | |
| RLLRBackbone=Baichuan2 7B2024.05 | 93 | |
| RLLR_MIXEDBackbone=Baichuan2 7B2024.05 | 93 | |
| RLHFBackbone=Baichuan2 7B2024.05 | 92.9 | |
| SFT w. rat.Backbone=Mistral 7B2024.05 | 92.7 | |
| RLLR_MIXEDBackbone=Mistral 7B2024.05 | 92.7 | |
| RLHFBackbone=Bloom 7B2024.05 | 92.7 | |
| RLLRBackbone=Bloom 7B2024.05 | 92.7 | |
| GENICLBackbone=LLaMA-7B, Evaluation Setting=Few-shot (ICL)2025.05 | 92.6 | |
| SFT w. rat.Backbone=LLaMA2 7B2024.05 | 92.5 | |
| SFTBackbone=Mistral 7B2024.05 | 92.5 | |
| SFT w. rat.Backbone=Baichuan2 7B2024.05 | 92.5 | |
| RLLR_MIXEDBackbone=Bloom 7B2024.05 | 92.5 | |
| LLM-RBackbone=LLaMA-7B, Evaluation Setting=Few-shot (ICL)2025.05 | 92.4 | |
| SFTBackbone=LLaMA2 7B2024.05 | 92.2 | |
| RLHFBackbone=Mistral 7B2024.05 | 92.2 | |
| RNN/LSTMEmbedding=GloVe2026.04 | 92.1 | |
| SFT w. rat.Backbone=Bloom 7B2024.05 | 91.8 | |
| EPRBackbone=LLaMA-7B, Evaluation Setting=Few-shot (ICL)2025.05 | 91.8 | |
| fastTexth=102026.04 | 91.5 | |
| ANYSIMLITE#Params (M)=1.32026.06 | 91.12 | |
| E5baseBackbone=LLaMA-7B, Evaluation Setting=Few-shot (ICL)2025.05 | 90.6 | |
| FADS-ICLBackbone=Llama-1 30B, Shots=128-shots2024.05 | 90.5 | |
| FADS-ICLBackbone=Llama-2 70B, Shots=128-shots2024.05 | 90.2 | |
| TMEmbedding=GloVe2026.04 | 90.12 | |
| BM25Backbone=LLaMA-7B, Evaluation Setting=Few-shot (ICL)2025.05 | 90 | |
| kNN-promptBackbone=Llama-1 13B, Shots=128-shots2024.05 | 89.9 | |
| kNN-promptBackbone=Llama-1 30B, Shots=128-shots2024.05 | 89.9 | |
| Finetune2022.12 | 89.85 | |
| SFTBackbone=Bloom 7B2024.05 | 89.8 | |
| FADS-ICLcandidate pool size (m)=2562024.05 | 89.8 | |
| SBERTBackbone=LLaMA-7B, Evaluation Setting=Few-shot (ICL)2025.05 | 89.8 | |
| MUPPET2022.12 | 89.77 | |
| FADS-ICLBackbone=Llama-1 7B, Shots=128-shots2024.05 | 89.7 | |
| BoW TFIDF2026.04 | 89.64 | |
| kNN-promptingBackbone=Llama-2 13B, Shots=128-shots2024.05 | 89.6 | |
| FADS-ICLBackbone=Llama-2 13B, Shots=128-shots2024.05 | 89.6 | |
| ColD-Fusion2022.12 | 89.58 | |
| Multitask2022.12 | 89.55 | |
| BERT-base + PGKD#Params (M)=-2026.06 | 89.5 | |
| DCModel=Llama-2 13b, ICL Setting=1-shot2024.05 | 89.34 | |
| FADS-ICLBackbone=Llama-1 13B, Shots=128-shots2024.05 | 89.2 | |
| ICLModel=Llama-2 13b, ICL Setting=1-shot2024.05 | 89.14 | |
| FADS-ICLBackbone=Llama-2 7B, Shots=128-shots2024.05 | 89.1 | |
| DCModel=Llama-2 7b, ICL Setting=1-shot2024.05 | 89.08 | |
| kNN-promptingBackbone=Llama-1 30B, Shots=128-shots2024.05 | 89 | |
| ICLBackbone=Llama-2 70B, Shots=128-shots2024.05 | 88.8 | |
| UniBiasModel=Llama-2 13b, ICL Setting=1-shot2024.05 | 88.68 | |
| DCBackbone Model=Qwen, Shot Count=16-shot2025.05 | 88.44 | |
| DCModel=Qwen, k-shot=162025.05 | 88.44 | |
| FADS-ICLNumber of training shots (m)=128, LLM scale=1.5B2024.05 | 88.4 | |
| FADS-ICLBackbone=GPT-2 1.5B, Shots=128-shots2024.05 | 88.4 | |
| kNN-promptingBackbone=Llama-1 13B, Shots=128-shots2024.05 | 88.4 | |
| FADS-ICLcandidate pool size (m)=1282024.05 | 88.4 | |
| TM2026.04 | 88.34 | |
| GPT Large FTBackbone=GPT Large, Shots=N/A (Fine-tuned)2024.05 | 88.3 | |
| kNN-promptingBackbone=Llama-2 7B, Shots=128-shots2024.05 | 88.3 | |
| UniBiasModel=Llama-2 7b, ICL Setting=1-shot2024.05 | 88.29 | |
| CCModel=Llama-2 13b, ICL Setting=1-shot2024.05 | 88.23 | |
| FADS-ICLNumber of training shots (m)=32, LLM scale=1.5B2024.05 | 88.2 | |
| FADS-ICLBackbone=GPT-2 0.8B, Shots=128-shots2024.05 | 88.1 | |
| BERT Large FTBackbone=BERT Large, Shots=N/A (Fine-tuned)2024.05 | 88 | |
| kNN-promptBackbone=Llama-2 13B, Shots=128-shots2024.05 | 87.9 | |
| SCBackbone Model=Mistral, Shot Count=16-shot2025.05 | 87.81 | |
| SCModel=Mistral, k-shot=162025.05 | 87.81 | |
| kNN-promptingNumber of training shots (m)=128, LLM scale=1.5B2024.05 | 87.8 | |
| kNN-promptingBackbone=GPT-2 1.5B, Shots=128-shots2024.05 | 87.8 | |
| FADS-ICLcandidate pool size (m)=642024.05 | 87.8 | |
| kNN-promptingBackbone=Llama-2 70B, Shots=128-shots2024.05 | 87.7 | |
| kNN-promptingBackbone=Llama-1 7B, Shots=128-shots2024.05 | 87.6 | |
| kNN-promptBackbone=Llama-2 70B, Shots=128-shots2024.05 | 87.5 | |
| SCBackbone Model=Llama, Shot Count=16-shot2025.05 | 87.42 | |
| SCModel=Llama, k-shot=162025.05 | 87.42 | |
| char-CNN2026.04 | 87.2 | |
| ICLBackbone=Llama-1 30B, Shots=128-shots2024.05 | 87.1 | |
| FADS-ICLNumber of training shots (m)=64, LLM scale=1.5B2024.05 | 87 | |
| kNN-promptingBackbone=GPT-2 0.8B, Shots=128-shots2024.05 | 86.9 | |
| PCModel=Llama-2 7b, ICL Setting=1-shot2024.05 | 86.81 | |
| kNN-promptingNumber of training shots (m)=64, LLM scale=1.5B2024.05 | 86.6 | |
| FADS-ICLNumber of training shots (m)=16, LLM scale=1.5B2024.05 | 86.5 | |
| DecTn (Shots)=162022.12 | 86.4 | |
| kNN-promptBackbone=Llama-1 7B, Shots=128-shots2024.05 | 86.4 | |
| SFTBackbone=RoBERTa_LARGE, Samples per class=162025.06 | 86.36 | |
| SBERTcandidate pool size (m)=2562024.05 | 86.3 | |
| ICLBackbone=Llama-1 7B, Shots=128-shots2024.05 | 86.2 | |
| ICLBackbone=Llama-1 13B, Shots=128-shots2024.05 | 86.2 |