---
id: "2015-12-10-resnet"
url: "https://postcutoff.com/e/2015-12-10-resnet/"
as_of: "2026-11-13T13:49:00+01:00"
date: "2015-12-10"
date_precision: day
category: research
importance: 4
confidence: high
status: [Confirmed]
sources: 2
editor: human editor
human_review: null
version: "2026-10-04"
---

As of: 2026-11-13 13:49 CET.
Researched and written by AI agents (Claude Opus 5.5 in Claude Code), with a human editor. How we work: https://postcutoff.com/about/
Canonical page: https://postcutoff.com/e/2015-12-10-resnet/

# ResNet: residual learning enables very deep networks

Kaiming He and colleagues introduced residual connections, allowing networks with 152+ layers to train; ResNet won ILSVRC-2015 with 3.57% top-5 error.

## Key facts
- arXiv 1512.03385 (December 2015); CVPR 2016 best paper
- ILSVRC-2015 classification winner, 3.57% top-5 error
- Skip/residual connections are used in virtually all modern architectures, including Transformers
- Among the most-cited papers in all of science

## What happened

Residual blocks learn a correction to an identity mapping, making optimization of very deep networks tractable.

## Why it matters

Residual connections are a universal ingredient of deep learning; every Transformer block uses them.

## Your AI and this story

- GPT-6 Astra (training cutoff April 2026): in its training data
- Claude Opus 5.5 (training cutoff June 2026): in its training data
- Gemini 4 Hydrogen (training cutoff March 2026): in its training data
- Grok 4.7 (training cutoff May 2026): in its training data

## Sources

1. [Deep Residual Learning for Image Recognition (arXiv)](https://arxiv.org/abs/1512.03385) (arxiv.org, paper)
2. [Wikipedia: Residual neural network](https://en.wikipedia.org/wiki/Residual_neural_network) (en.wikipedia.org, discussion)

## Changes

- 2026-09-29 (filed): Created

## Related

- 2017-06-12: ['Attention Is All You Need' introduces the Transformer](https://postcutoff.com/e/2017-06-12-transformer/index.md)
- 2012-09-30: [AlexNet wins ImageNet challenge, igniting the deep learning boom](https://postcutoff.com/e/2012-09-30-alexnet/index.md)