Home/Researchers/Colin Raffel

Researcher Profile

Colin Raffel

Text-to-text transfer and pretraining (T5)

Researcher at University of North Carolina at Chapel Hill

Co-authored T5: a practical template for unified NLP training and evaluation.

Organizations

University of North Carolina at Chapel HillEindhoven University of Technology

Topics

Evaluation & Benchmarks

About This Page

This profile is meant to help you get oriented quickly: why this researcher matters, what to read first, and where to explore next.

Last updated

March 20, 2026

Best First Clicks

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformerpaper

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Known For

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01

Text-to-text transfer and pretraining (T5)

02

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

03

T5

04

NLP

05

Pretraining

Start Here

Canonical papers, project pages, or repositories that anchor this profile.

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformerpaper

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Related Researchers

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Shared canonical source

Text-to-text transfer and pretraining (T5)

1 source

Co-authored T5: a practical template for unified NLP training and evaluation.

Evaluation & Benchmarks

Start HereExploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Shared canonical source

Text-to-text transfer and pretraining (T5)

1 source

Co-authored T5: a practical template for unified NLP training and evaluation.

Evaluation & Benchmarks

Start HereExploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Shared canonical source

Text-to-text transfer and pretraining (T5)

1 source

Co-authored T5: a practical template for unified NLP training and evaluation.

Evaluation & Benchmarks

Start HereExploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Shared canonical source

Text-to-text transfer and pretraining (T5)

1 source

Co-authored T5: a practical template for unified NLP training and evaluation.

Evaluation & Benchmarks

Start HereExploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Shared topic

Scaling laws, LLM training dynamics

3 sources

One of the clearest anchors for understanding why scaling laws became such a central planning tool for frontier-model research and training strategy.

Anthropic Evaluation & Benchmarks Reinforcement Learning

Start HereScaling Laws for Neural Language Models

Shared topic

NLP systems and evaluation

4 sources

A strong person to follow for practical language systems because his work sits right at the intersection of pretraining, retrieval, and question answering, where product-grade NLP systems either become robust or fall apart.

Evaluation & Benchmarks Systems & Infrastructure

Start HereKenton Lee