Popular GitHub Repositories for Esco Taxonomy

Diffusion model papers, survey, and taxonomy

Collecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey".

A Survey and Taxonomy of the Recent GANs Development，computer vision & time series

[arXiv'24] Large Language Model Enhanced Recommender Systems: Taxonomy, Trend, Application and Future

Machine Learning based Intrusion Detection Systems are difficult to evaluate due to a shortage of datasets representing accurately network traffic and their associated threats. In this project we attempt at solving this problem by presenting two taxonomies

Topic Inference with Zeroshot models

Artifact repository for the paper "Lost in Translation: A Study of Bugs Introduced by Large Language Models while Translating Code", In Proceedings of The 46th IEEE/ACM International Conference on Software Engineering (ICSE 2024), Lisbon, Portugal, April 2024

中文概念图谱OpenConcepts

Welcome! ? This is the working draft of the Aalto Dictionary of Machine Learning (ADictML) — a growing collection of short, clear definitions for key terms in machine learning.

Generalized Video Anomaly Event Detection: Systematic Taxonomy and Comparison of Deep Models

Task Complexity Classifier using Transformer-based NLP model based on Bloom's Taxonomy

Taxonomy refinement method to improve domain-specific taxonomy systems.

PyTorch implementation of Metric-Guided Prototype Learning for hierarchical classification.

发表在WWW 2025会议论文“TELEClass：基于最小监督的词汇增强和大型语言模型增强的分层文本分类”中使用的源代码。

Taxonomy of Benchmarks in Graph Representation Learning

Dynamically constructs and adapts an LLM-generated taxonomy to a given corpus across multiple dimensions.

Classify your e-commerce products into categories of well-known e-commerce platforms. It uses OpenAI embeddings and LangChain.

Extract ESCO skills and ISCO occupations from texts such as job descriptions or CVs

Comprehensive taxonomy of AI security vulnerabilities, LLM adversarial attacks, prompt injection techniques, and machine learning security research. Covers 71+ attack vectors including model poisoning, agentic AI exploits, and privacy breaches.

This application helps users explore and understand the vast array of existing methods, ranging from traditional statistical approaches to modern machine learning algorithms. It visualizes a structured, process-centric taxonomy of anomaly detection techniques, enabling a deeper insight into the research landscape.