Knowledge-aware Zero-Shot Learning: Survey and Perspective
Zero-shot learning (ZSL) which aims at predicting classes that have never appeared during the training using external knowledge (a.k.a. side information) has been widely investigated. In this paper we present a literature review towards ZSL in the perspective of external knowledge, where we categorize the external knowledge, review their methods and compare different external knowledge. With the literature review, we further discuss and outlook the role of symbolic knowledge in addressing ZSL and other machine learning sample shortage issues.
Code (1)
Tasks
BIG-bench Machine LearningSurveyZero-Shot LearningSimilar Papers 제목 키워드 기반
Zero-shot and Few-shot Learning with Knowledge Graphs: A Comprehensive Survey
Machine learning especially deep neural networks have achieved great success but many of them often rely on a number of labeled samples for supervision. As sufficient labeled training data are not always ready due to e.g…
Data AugmentationFew-Shot Learningimage-classificationImage Classification+9Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities
Recently, zero-shot (or training-free) Neural Architecture Search (NAS) approaches have been proposed to liberate NAS from the expensive training process. The key idea behind zero-shot NAS approaches is to design proxies…
Neural Architecture SearchCompositional Zero-Shot Learning: A Survey
Compositional Zero-Shot Learning (CZSL) is a critical task in computer vision that enables models to recognize unseen combinations of known attributes and objects during inference, addressing the combinatorial challenge …
Compositional Zero-Shot LearningMulti-Label Zero-Shot Learning with Transfer-Aware Label Embedding Projection
Zero-shot learning transfers knowledge from seen classes to novel unseen classes to reduce human labor of labelling data for building new classifiers. Much effort on zero-shot learning however has focused on the standard…
image-classificationImage ClassificationMulti-Label Image ClassificationMulti-label zero-shot learning+2From Natural Language to SQL: Review of LLM-based Text-to-SQL Systems
Since the onset of LLMs, translating natural language queries to structured SQL commands is assuming increasing. Unlike the previous reviews, this survey provides a comprehensive study of the evolution of LLM-based text-…
Computational EfficiencyData AugmentationFew-Shot LearningIn-Context Learning+4