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canonical_url: "https://aidr.today/0d0e88ba?lang=en"
title: "Inverse Reasoning Models for Efficient Post-Training and Verification from Answer-Only Data"
lang: "en"
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published_at: "2026-10-15T04:00:00.000Z"
category: "Research"
topics: ["reasoning"]
source_urls: ["https://arxiv.org/abs/2610.18878"]
summary: "A self-distillation technique using answer-only data trains an inverse reasoning LLM to generate chain-of-thought traces, enabling more efficient post-training without requiring supervised reasoning data."
---

# Inverse Reasoning Models for Efficient Post\-Training and Verification from Answer\-Only Data

> [Open the canonical story](<https://aidr.today/0d0e88ba?lang=en>)

**Published:** 2026-10-15T04:00:00.000Z
**Category:** Research
**Topics:** reasoning

## Summary

A self\-distillation technique using answer\-only data trains an inverse reasoning LLM to generate chain\-of\-thought traces, enabling more efficient post\-training without requiring supervised reasoning data\.

## Sources

- [Story source](<https://arxiv.org/abs/2610.18878>)