Code I/O: Condensing Reasoning Patterns via Code Input-Output Prediction

Mon, 07 Jul 2025 00:00:00 +0900

Paper

CODE I/O: From Code I/O + Natural-Language CoT to General-Purpose Reasoning — Lifting 7B-30B LLMs by +2 Points on Average with Data Design Alone

TL;DR

A single data pipeline of “code function → input/output prediction + structured Chain-of-Thought (CoT)” lets 3.5 M samples deliver larger and more balanced gains (+2.9 points) than 14 M-scale SOTA data. By nailing verifiability, low cost, and diversity at once, CODE I/O empirically demonstrates that “data quality > data quantity.”

LLM on Jaehun's Blog

Code I/O: Condensing Reasoning Patterns via Code Input-Output Prediction

CODE I/O: From Code I/O + Natural-Language CoT to General-Purpose Reasoning — Lifting 7B-30B LLMs by +2 Points on Average with Data Design Alone

TL;DR