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Serhii Zamrii

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Trying my best to become 1% less wrong every day.

Seriously concerned about future of humanity and AI alignment

The Overlap Paradigm: Rethinking Data's Role in Weak-to-Strong Generalization (W2SG)

Note: This post summarizes my capstone project for the AI Alignment course by BlueDot Impact. You can learn more about their amazing courses here and consider applying! Introduction Recent research in weak-to-strong generalization (W2SG) has revealed a crucial insight: enhancing weak supervisors to train strong models relies more on the...

Feb 3, 2025•2

Serhii Zamrii

Trying my best to become 1% less wrong every day.

Seriously concerned about future of humanity and AI alignment

Serhii Zamrii — LessWrong

Serhii Zamrii

Message

Trying my best to become 1% less wrong every day.

Seriously concerned about future of humanity and AI alignment

The Overlap Paradigm: Rethinking Data's Role in Weak-to-Strong Generalization (W2SG)

Feb 3, 2025•2

Serhii Zamrii

Trying my best to become 1% less wrong every day.

Seriously concerned about future of humanity and AI alignment

The Overlap Paradigm: Rethinking Data's Role in Weak-to-Strong Generalization (W2SG)

Serhii Zamrii

Note: This post summarizes my capstone project for the AI Alignment course by BlueDot Impact. You can learn more about their amazing courses here and consider applying!

Introduction

Recent research in weak-to-strong generalization (W2SG) has revealed a crucial insight: enhancing weak supervisors to train strong models relies more on the characteristics of the training data rather than on new algorithms. This article reviews the research conducted by Shin et al. (2024), who identified overlap density — a measurable data attribute that can predict and support successful W2SG. Their findings suggest we've been looking at the alignment problem through the wrong lens — instead of only focusing on model architectures, we should also be engineering... (read 3076 more words →)