#zero-shot-learning

Day 26: Zero-Shot vs Few-Shot Prompting Explained

A practical developer-focused guide to when a direct prompt is enough, when examples matter, and why few-shot prompting is not the same as…

Metamorphosis 39/58: Book II ‘Bridge’ — Appendix — Chrysalis Cycle: Awakened Asleep (Poetry)

My version:

Day 71 1.6: Agentic AI in Open Banking — Zero-shot ML inference on Knowledge Graph

The architecture that eliminates ML training while maximizing intelligence

I Stopped Manually Labeling Images. A Practical Guide to Zero-Shot Object Detection with YOLO-World

從 GPT 到 LLM-Pro：MMLU 如何衡量 AI 的真正智慧

MMLU（Massive Multitask Language Understanding）是衡量大型語言模型（LLMs）能力的關鍵基準。本文深入解析 MMLU 的起源、數據集架構、評估方法與衍生版本（MMLU-Pro、MMLU-CF），並探討它對 AI 研究與應用的深遠影響

LesionLocator: A Breakthrough in Zero-Shot Tumor Segmentation and Tracking Across the Entire Human…

Introduction: Can AI Truly “See” Tumors Anywhere in the Body?

LesionLocator: Zero-Shot Universal Tumor Segmentation and Tracking in 3D Whole-Body Imaging

Introduction

YOLOE: Revolutionizing Object Detection with Visual Prompts [Part-1]

Introduction

Zero-Shot Text Classification: Reducing Annotation Effort with AI

What if you could classify text into categories without any labeled examples?

Zero-Shot Classification: Unlocking the Power of Generalization in AI

In the ever-evolving world of machine learning, one of the major challenges has been training models to recognize new categories without…

Machine Learning with Few Labels

Curious how you might be able to use Machine Learning for common tasks like classification with only a few labeled examples?