Toward Mechanistic Explanation of Deductive Reasoning in Language Models

Fuente: arXiv
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Autori principali: Maltoni, Davide, Ferrara, Matteo
Natura: Preprint
Pubblicazione: 2025
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author Maltoni, Davide
Ferrara, Matteo
author_facet Maltoni, Davide
Ferrara, Matteo
contents Recent large language models have demonstrated relevant capabilities in solving problems that require logical reasoning; however, the corresponding internal mechanisms remain largely unexplored. In this paper, we show that a small language model can solve a deductive reasoning task by learning the underlying rules (rather than operating as a statistical learner). A low-level explanation of its internal representations and computational circuits is then provided. Our findings reveal that induction heads play a central role in the implementation of the rule completion and rule chaining steps involved in the logical inference required by the task.
format Preprint
id arxiv_https___arxiv_org_abs_2510_09340
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Toward Mechanistic Explanation of Deductive Reasoning in Language Models
Maltoni, Davide
Ferrara, Matteo
Artificial Intelligence
Computation and Language
Recent large language models have demonstrated relevant capabilities in solving problems that require logical reasoning; however, the corresponding internal mechanisms remain largely unexplored. In this paper, we show that a small language model can solve a deductive reasoning task by learning the underlying rules (rather than operating as a statistical learner). A low-level explanation of its internal representations and computational circuits is then provided. Our findings reveal that induction heads play a central role in the implementation of the rule completion and rule chaining steps involved in the logical inference required by the task.
title Toward Mechanistic Explanation of Deductive Reasoning in Language Models
topic Artificial Intelligence
Computation and Language
url https://arxiv.org/abs/2510.09340