arXiv · 2609.17804
A Four-Stage Decomposition of Word-Problem Solving and Mechanistic Fragility in LLM Math Reasoning
Abstract
Large language models solve grade-school math word problems with high accuracy, yet a single irrelevant clause inserted into the problem can collapse it. We reconcile these observations with a mechanistic account. We show that the model's internal computation decomposes into a four-stage sequential pipeline, Schema Abstraction, Operation Planning, Operand Binding, and Computation, each stage producing a distinct intermediate representation in an identifiable band of layers. Using the same scaffold to diagnose distractor-induced failure, we localize the corruption to a single stage, Operation Planning, implemented by a set of attention heads whose causal role we validate bidirectionally. In short, we provide a mechanistic interpretation of math word problem reasoning in LLMs, and their failure when distracted.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Zhongdi Qu, Carla P. Gomes. 2026-09-15. A Four-Stage Decomposition of Word-Problem Solving and Mechanistic Fragility in LLM Math Reasoning. https://arxiv.org/abs/2609.17804
Cite the original work for its findings. Save a collection to share your selection of sources.