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Show HN: Duplicate 3 layers in a 24B LLM, logical deduction .22→.76. No training

🧠💻 "Unlocking Cognitive Layers: Duplicating Reasoning Circuits in 24B LLMs Boosts Logical Deduction"

Transformers in large language models (LLMs) have been found to contain discrete "reasoning circuits" – contiguous blocks of 3-4 layers that act as indivisible cognitive units. By duplicating these blocks, researchers achieved significant boosts in logical deduction and other reasoning tasks without altering model weights or requiring training, effectively enhancing the model's cognitive abilities.

1:05 am, March 19, 2026

guid

https://news.ycombinator.com/item?id=47431671

source_url

https://github.com/alainnothere/llm-circuit-finder

author_name

xlayn

id: 955
uid: 2pUsw
insdate: 2026-03-19 01:05:14
title: Show HN: Duplicate 3 layers in a 24B LLM, logical deduction .22→.76. No training
additional: 🧠💻 "Unlocking Cognitive Layers: Duplicating Reasoning Circuits in 24B LLMs Boosts Logical Deduction"

Transformers in large language models (LLMs) have been found to contain discrete "reasoning circuits" – contiguous blocks of 3-4 layers that act as indivisible cognitive units. By duplicating these blocks, researchers achieved significant boosts in logical deduction and other reasoning tasks without altering model weights or requiring training, effectively enhancing the model's cognitive abilities.
category: Hacker News
md5:
guid: https://news.ycombinator.com/item?id=47431671
source_url: https://github.com/alainnothere/llm-circuit-finder
updated:
image:
author_name: xlayn
author_link:
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