Prompt Research

관련된 논문 참고자료 (출처: 모두의연구소)

Zero Shot Semantic Segmentation

논문 링크 - https://arxiv.org/abs/1906.00817

설명 링크 - https://deep-learning-study.tistory.com/872

Zero Shot Learning

논문 논문 링크 - https://arxiv.org/abs/2011.08641

설명 링크 - https://deep-learning-study.tistory.com/873

CaGNet - Context-aware Feature Generation for Zero-shot Semantic Segmentation

논문 링크 - https://arxiv.org/abs/2008.06893

설명 링크 - https://deep-learning-study.tistory.com/874

SIGN - Spatial-information Incorporated Generative Network for Generalized Zero-shot Semantic Segmentation

논문 링크 - https://arxiv.org/abs/2108.12517

설명 링크 - https://deep-learning-study.tistory.com/875

Metric-based approaches to meta-learning

설명 링크 - http://dmqm.korea.ac.kr/activity/seminar/301

Few-Shot Learning

https://paperswithcode.com/task/few-shot-learning

Language Models are Few-Shot Learners

설명 링크 - https://lee-soohyun.tistory.com/274

Few-shot Image Generation via Cross-domain Correspondence

논문 링크 - https://arxiv.org/abs/2104.06820

설명 링크 - https://jjuon.tistory.com/27

Meta-Learning with Task-Adaptive Loss function for Few-Shot Learning

논문 링크 - https://arxiv.org/abs/2110.03909

설명 링크 - https://jjuon.tistory.com/30

One Shot Learning, Siamese Network, Triplet Loss, Binary Loss

설명 링크 - https://wooono.tistory.com/239

Siamese Neural Networks 개념 이해하기

https://tyami.github.io/deep%20learning/Siamese-neural-networks/

Reference

ChatGPT Prompt Learning Research LAB | LAB | 모두의연구소modulabs.co.kr