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 51–75 of 305 papers

TitleStatusHype
LLMs are One-Shot URL Classifiers and Explainers—0
Direct Data-Driven Discounted Infinite Horizon Linear Quadratic Regulator with Robustness GuaranteesCode0
Abstracted Gaussian Prototypes for One-Shot Concept LearningCode0
One-Shot Learning Meets Depth Diffusion in Multi-Object Videos—0
Emulating Brain-like Rapid Learning in Neuromorphic Edge ComputingCode0
Correlation Weighted Prototype-based Self-Supervised One-Shot Segmentation of Medical Images—0
MU-MAE: Multimodal Masked Autoencoders-Based One-Shot Learning—0
One-Shot Collaborative Data DistillationCode0
Encoding Matching Criteria for Cross-domain Deformable Image RegistrationCode0
Object Detection using Oriented Window Learning Vi-sion Transformer: Roadway Assets Recognition—0
Npix2Cpix: A GAN-Based Image-to-Image Translation Network With Retrieval- Classification Integration for Watermark Retrieval From Historical Document Images—0
Active Use of Latent Constituency Representation in both Humans and Large Language ModelsCode0
Response Matching for generating materials and molecules—0
Reddit-Impacts: A Named Entity Recognition Dataset for Analyzing Clinical and Social Effects of Substance Use Derived from Social Media—0
Learning Symbolic Task Representation from a Human-Led Demonstration: A Memory to Store, Retrieve, Consolidate, and Forget ExperiencesCode0
Exploring the potential of prototype-based soft-labels data distillation for imbalanced data classification—0
A Feature-based Generalizable Prediction Model for Both Perceptual and Abstract ReasoningCode0
Leveraging Weakly Annotated Data for Hate Speech Detection in Code-Mixed Hinglish: A Feasibility-Driven Transfer Learning Approach with Large Language Models—0
More than the Sum of Its Parts: Ensembling Backbone Networks for Few-Shot Segmentation—0
AHAM: Adapt, Help, Ask, Model -- Harvesting LLMs for literature mining—0
Prototype-Based Approach for One-Shot Segmentation of Brain Tumors using Few-Shot Learning—0
Little Giants: Exploring the Potential of Small LLMs as Evaluation Metrics in Summarization in the Eval4NLP 2023 Shared Task—0
SparseDFF: Sparse-View Feature Distillation for One-Shot Dexterous Manipulation—0
An Event based Prediction Suffix Tree—0
Temporal credit assignment for one-shot learning utilizing a phase transition material—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified