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Few-Shot Text Classification

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

Papers

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Showing 11–20 of 100 papers

Title	Date	Tasks	Status	Hype	Score
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference	Jan 21, 2020	Few-Shot Text ClassificationGeneral Classification	CodeCode Available	1	5
Induction Networks for Few-Shot Text Classification	Feb 27, 2019	Few-Shot Text ClassificationGeneral Classification	CodeCode Available	1	5
Few-Shot Learning with Siamese Networks and Label Tuning	Mar 28, 2022	Few-Shot LearningFew-Shot Text Classification	CodeCode Available	1	5
Distinct Label Representations for Few-Shot Text Classification	Aug 1, 2021	ClassificationFew-Shot Text Classification	CodeCode Available	1	5
A Neural Few-Shot Text Classification Reality Check	Jan 28, 2021	ClassificationFew-Shot Text Classification	CodeCode Available	1	5
ContrastNet: A Contrastive Learning Framework for Few-Shot Text Classification	May 16, 2023	ClassificationContrastive Learning	CodeCode Available	1	5
Few-Shot Text Classification with Triplet Networks, Data Augmentation, and Curriculum Learning	Mar 12, 2021	ClassificationData Augmentation	CodeCode Available	1	5
Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER	Oct 16, 2021	Domain AdaptationFew-Shot Text Classification	CodeCode Available	1	5
Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification	Aug 4, 2021	ClassificationFew-Shot Text Classification	CodeCode Available	1	5
Meta-Learning Adversarial Domain Adaptation Network for Few-Shot Text Classification	Jul 26, 2021	Domain AdaptationFew-Shot Text Classification	CodeCode Available	1	5

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All datasets RAFT Average on NLP datasets Amazon Counterfeit ODIC 10-way (10-shot)ODIC 10-way (5-shot)ODIC 5-way (10-shot)ODIC 5-way (5-shot)SST-5

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	T-Few	Avg	0.76	—	Unverified
2	Human (crowdsourced)	Avg	0.74	—	Unverified
3	GPT-3	Avg	0.63	—	Unverified
4	AdaBoost	Avg	0.51	—	Unverified
5	GPT-Neo	Avg	0.48	—	Unverified
6	GPT-2	Avg	0.46	—	Unverified
7	BART MNLI zero-shot	Avg	0.38	—	Unverified
8	Plurality-class	Avg	0.33	—	Unverified
9	GPT-3 zero-shot	Avg	0.29	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SetFit + OCD(5)	Accuracy	0.65	—	Unverified
2	SetFit + OCD	Accuracy	0.64	—	Unverified
3	T-few 3B	Accuracy	0.63	—	Unverified
4	SetFit	Accuracy	0.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SetFit + OCD	Accuracy	0.41	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Induction Networks	Accuracy	81.64	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Induction Networks	Accuracy	78.27	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Induction Networks	Accuracy	88.49	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Induction Networks	Accuracy	87.16	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SetFit + OCD	Accuracy	0.48	—	Unverified