Improving Mathematical Reasoning Capabilities in Large Language Models via Reasoning Process Error Classification

Automatically screened research note. This is not an independently verified breakthrough and not a full-paper review.

Source

Research community

Source publication

2026-09-14

First observed

2026-10-29T21:52:00+00:00

Extraction scope

source metadata and abstract / description

What was published?

The linked preprint is titled Improving Mathematical Reasoning Capabilities in Large Language Models via Reasoning Process Error Classification. The screening rules associate it with mathematical reasoning. This association is a topic classification, not a finding that the claims are correct.

Source description

The reasoning ability of large language models (LLMs) is a critical factor for practical LLM-based applications. To investigate the current reasoning capability of LLMs, we

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What has not been established

This site has not independently established novelty, peer review, reproducibility or theorem correctness. An arXiv listing is a preprint record, not a journal acceptance. A provider announcement describes its own research.

Provenance and reusable data

https://arxiv.org/abs/2609.15145

Detected topic terms: mathematical, reasoning. Method: deterministic metadata screening; no model-generated proof verdict.

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