SOTAVerified

Few-Shot Text Classification

Few-shot Text Classification predicts the semantic label of a given text with a handful of supporting instances 1

Papers

Showing 41–50 of 100 papers

TitleStatusHype
Disentangling Task Relations for Few-shot Text Classification via Self-Supervised Hierarchical Task Clustering—0
Dynamic Memory Induction Networks for Few-Shot Text Classification—0
Effective Few-Shot Classification with Transfer Learning—0
EICO: Improving Few-Shot Text Classification via Explicit and Implicit Consistency Regularization—0
Emotion-Conditioned Text Generation through Automatic Prompt Optimization—0
Empirical Study of Mutual Reinforcement Effect and Application in Few-shot Text Classification Tasks via Prompt—0
Enhancing Black-Box Few-Shot Text Classification with Prompt-Based Data Augmentation—0
Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference—0
Few-Shot Learning with Siamese Networks and Label Tuning—0
Few-shot Text Classification with Dual Contrastive Consistency—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1T-FewAvg0.76—Unverified
2Human (crowdsourced)Avg0.74—Unverified
3GPT-3Avg0.63—Unverified
4AdaBoostAvg0.51—Unverified
5GPT-NeoAvg0.48—Unverified
6GPT-2Avg0.46—Unverified
7BART MNLI zero-shotAvg0.38—Unverified
8Plurality-classAvg0.33—Unverified
9GPT-3 zero-shotAvg0.29—Unverified
#ModelMetricClaimedVerifiedStatus
1SetFit + OCD(5)Accuracy0.65—Unverified
2SetFit + OCDAccuracy0.64—Unverified
3T-few 3BAccuracy0.63—Unverified
4SetFitAccuracy0.62—Unverified
#ModelMetricClaimedVerifiedStatus
1SetFit + OCDAccuracy0.41—Unverified
#ModelMetricClaimedVerifiedStatus
1Induction NetworksAccuracy81.64—Unverified
#ModelMetricClaimedVerifiedStatus
1Induction NetworksAccuracy78.27—Unverified
#ModelMetricClaimedVerifiedStatus
1Induction NetworksAccuracy88.49—Unverified
#ModelMetricClaimedVerifiedStatus
1Induction NetworksAccuracy87.16—Unverified
#ModelMetricClaimedVerifiedStatus
1SetFit + OCDAccuracy0.48—Unverified