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

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Showing 121–130 of 305 papers

TitleStatusHype
Learning feed-forward one-shot learners—0
Learning from limited datasets: Implications for Natural Language Generation and Human-Robot Interaction—0
AROS: Affordance Recognition with One-Shot Human Stances—0
AHAM: Adapt, Help, Ask, Model -- Harvesting LLMs for literature mining—0
Improving One-Shot Learning through Fusing Side Information—0
Improving Knowledge Extraction from LLMs for Task Learning through Agent Analysis—0
Contour Primitive of Interest Extraction Network Based on One-Shot Learning for Object-Agnostic Vision Measurement—0
High-dimensional separability for one- and few-shot learning—0
HDXplore: Automated Blackbox Testing of Brain-Inspired Hyperdimensional Computing—0
Continuous Learning in Neural Machine Translation using Bilingual Dictionaries—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified