The Lookahead Limitation: Why Multi-Operand Addition is Hard for LLMs

Fuente: arXiv
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Autori principali: Baeumel, Tanja, van Genabith, Josef, Ostermann, Simon
Natura: Preprint
Pubblicazione: 2025
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author Baeumel, Tanja
van Genabith, Josef
Ostermann, Simon
author_facet Baeumel, Tanja
van Genabith, Josef
Ostermann, Simon
contents Autoregressive large language models (LLMs) exhibit impressive performance across various tasks but struggle with simple arithmetic, such as addition of two or more operands. We show that this struggle arises from LLMs' use of a simple one-digit lookahead heuristic, which works fairly well (but not perfect) for two-operand addition but fails in multi-operand cases, where the carry-over logic is more complex. Our probing experiments and digit-wise accuracy evaluation show that LLMs fail precisely where a one-digit lookahead is insufficient to account for cascading carries. We analyze the impact of tokenization strategies on arithmetic performance and show that all investigated models, regardless of tokenization, are inherently limited in the addition of multiple operands due to their reliance on a one-digit lookahead heuristic. Our findings reveal fundamental limitations that prevent LLMs from generalizing to more complex numerical reasoning.
format Preprint
id arxiv_https___arxiv_org_abs_2502_19981
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Lookahead Limitation: Why Multi-Operand Addition is Hard for LLMs
Baeumel, Tanja
van Genabith, Josef
Ostermann, Simon
Computation and Language
Autoregressive large language models (LLMs) exhibit impressive performance across various tasks but struggle with simple arithmetic, such as addition of two or more operands. We show that this struggle arises from LLMs' use of a simple one-digit lookahead heuristic, which works fairly well (but not perfect) for two-operand addition but fails in multi-operand cases, where the carry-over logic is more complex. Our probing experiments and digit-wise accuracy evaluation show that LLMs fail precisely where a one-digit lookahead is insufficient to account for cascading carries. We analyze the impact of tokenization strategies on arithmetic performance and show that all investigated models, regardless of tokenization, are inherently limited in the addition of multiple operands due to their reliance on a one-digit lookahead heuristic. Our findings reveal fundamental limitations that prevent LLMs from generalizing to more complex numerical reasoning.
title The Lookahead Limitation: Why Multi-Operand Addition is Hard for LLMs
topic Computation and Language
url https://arxiv.org/abs/2502.19981