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 191–200 of 305 papers

TitleStatusHype
Leveraging Siamese Networks for One-Shot Intrusion Detection Model—0
Leveraging Weakly Annotated Data for Hate Speech Detection in Code-Mixed Hinglish: A Feasibility-Driven Transfer Learning Approach with Large Language Models—0
Lifelong Machine Learning for Topic Modeling and Beyond—0
Little Giants: Exploring the Potential of Small LLMs as Evaluation Metrics in Summarization in the Eval4NLP 2023 Shared Task—0
LLMs are One-Shot URL Classifiers and Explainers—0
Low Data Drug Discovery with One-shot Learning—0
Mathematics of Digital Twins and Transfer Learning for PDE Models—0
MAVOT: Memory-Augmented Video Object Tracking—0
Max-Margin Invariant Features from Transformed Unlabeled Data—0
Max-Margin Invariant Features from Transformed Unlabelled Data—0
Show:102550
← PrevPage 20 of 31Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified