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Few-Shot Learning

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하위 태스크: 12
평가표: 27
보존된 평가 기록: 52

Few-Shot Learning is an example of meta-learning, where a learner is trained on several related tasks, during the meta-training phase, so that it can generalize well to unseen (but related) tasks with just few examples, during the meta-testing phase. An effective approach to the Few-Shot Learning problem is to learn a common representation for various tasks and train task specific classifiers on top of this representation.

Source: Penalty Method for Inversion-Free Deep Bilevel Optimization

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/rpeloff/multimodal-one-shot-learning

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Multimodal One-Shot Learning of Speech and Images

https://github.com/rpnode-fss/rpnode_fss

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Robust Prototypical Few-Shot Organ Segmentation with Regularized Neural-ODEs

https://github.com/rrmenon10/ADAPET

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Improving and Simplifying Pattern Exploiting Training

https://github.com/rsamf/text-guided-mixup

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Text-Guided Mixup Towards Long-Tailed Image Categorization

https://github.com/rtmaww/EntLM

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Template-free Prompt Tuning for Few-shot NER

https://github.com/rudylyh/CTN_data

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Contour Transformer Network for One-shot Segmentation of Anatomical Structures

https://github.com/runnanchen/clip2scene

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CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP

https://github.com/ruxie189/wss_pole

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Prompting classes: Exploring the Power of Prompt Class Learning in Weakly Supervised Semantic Segmentation

https://github.com/rvinas/polythetic_metalearning

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Attentional Meta-learners for Few-shot Polythetic Classification

https://github.com/s-a-malik/multi-few

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Multi-Modal Fusion by Meta-Initialization

https://github.com/s-l-chausson/easyclaimsdetection

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Detecting Statements in Text: A Domain-Agnostic Few-Shot Solution

https://github.com/s4nyam/ramario

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RAMario: Experimental Approach to Reptile Algorithm -- Reinforcement Learning for Mario

https://github.com/saakethmm/nc-prototypical-networks

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On the Role of Neural Collapse in Meta Learning Models for Few-shot Learning

https://github.com/saic-fi/bayesian-prompt-learning

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Bayesian Prompt Learning for Image-Language Model Generalization

https://github.com/saikat107/natgen

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NatGen: Generative pre-training by "Naturalizing" source code

https://github.com/salesforce/DNNC-few-shot-intent

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Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference

https://github.com/salesforce/DialogStudio

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DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI

https://github.com/sam1224/aenet

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Eliminating Feature Ambiguity for Few-Shot Segmentation

https://github.com/sam1224/hmnet

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Hybrid Mamba for Few-Shot Segmentation

https://github.com/sam1224/sccan

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Self-Calibrated Cross Attention Network for Few-Shot Segmentation

https://github.com/samsunglabs/swissdino

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Swiss DINO: Efficient and Versatile Vision Framework for On-device Personal Object Search

https://github.com/samuelhess/mll_fsl

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A Maximum Log-Likelihood Method for Imbalanced Few-Shot Learning Tasks

https://github.com/samuelstevens/mindthegap

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Mind the Gap: Evaluating Vision Systems in Small Data Applications

https://github.com/sankhasubhra/maml-ibp-ibi

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Interval Bound Interpolation for Few-shot Learning with Few Tasks

https://github.com/sap-samples/acl2023-micse

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miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings

https://github.com/sarinda251/cdfsl-v

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CDFSL-V: Cross-Domain Few-Shot Learning for Videos

https://github.com/sathvikb007/ECG-TSC-FSL

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Similarity Learning based Few Shot Learning for ECG Time Series Classification

https://github.com/savinay95n/PatchRefineNet

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PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise Binarization

https://github.com/scutcyr/soulchat2.0

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PsyDT: Using LLMs to Construct the Digital Twin of Psychological Counselor with Personalized Counseling Style for Psychological Counseling

https://github.com/sebischair/fusionsent

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Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes

https://github.com/seongmin-kye/MCT

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Meta-Learned Confidence for Few-shot Learning

https://github.com/seongwoongcho/meta-controller

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Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control

https://github.com/sgl-project/sglang

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SGLang: Efficient Execution of Structured Language Model Programs

https://github.com/sgottsch/tab2kg

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Tab2KG: Semantic Table Interpretation with Lightweight Semantic Profiles

https://github.com/sha168/ADNet

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Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels

https://github.com/shadowxzt/dacm-few-shot.pytorch

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Doubly Deformable Aggregation of Covariance Matrices for Few-shot Segmentation

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