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 11–20 of 305 papers

TitleStatusHype
Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction ModelsCode0
Take Package as Language: Anomaly Detection Using TransformerCode0
One-Shot Manipulation Strategy Learning by Making Contact Analogies—0
Supervised Learning without Backpropagation using Spike-Timing-Dependent Plasticity for Image RecognitionCode0
RePD: Defending Jailbreak Attack through a Retrieval-based Prompt Decomposition Process—0
SeqNet: Sequential Networks for One-Shot Traffic Sign Recognition With Transfer LearningCode0
LLMs are One-Shot URL Classifiers and Explainers—0
Direct Data-Driven Discounted Infinite Horizon Linear Quadratic Regulator with Robustness GuaranteesCode0
One-Shot Learning for Pose-Guided Person Image Synthesis in the WildCode1
Abstracted Gaussian Prototypes for One-Shot Concept LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified