SOTAVerified

One-Shot Learning

One-shot learning is the task of learning information about object categories from a single training example.

( Image credit: Siamese Neural Networks for One-shot Image Recognition )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 21–30 of 305 papers

TitleStatusHype
Efficient implementations of echo state network cross-validationCode1
Adjoined Networks: A Training Paradigm with Applications to Network CompressionCode1
Efficient Cross-Validation of Echo State NetworksCode1
An Overview of Deep Learning Architectures in Few-Shot Learning DomainCode1
One-Shot Instance SegmentationCode1
One-Shot Learning as Instruction Data Prospector for Large Language ModelsCode1
Differentiable Wavetable SynthesisCode1
Detecting Hate Speech with GPT-3Code1
Dynamic Few-Shot Visual Learning without ForgettingCode1
Grounded Language Learning Fast and SlowCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified