When LLMs Stop Following Steps: A Diagnostic Study of Procedural Execution in Language Models
arXiv:2605.00817v2 Announce Type: replace Abstract: Large language models (LLMs) often achieve strong performance on reasoning benchmarks, but final-answer accuracy alone does not show whether they faithfully execute the procedure specified in a prompt. We study this question through a controlled diagnostic benchmark for procedural execution, where models are given a step-wise arithmetic algorithm and two numeric inputs, and must return the final computed value. The benchmark uses simple arithmetic operations but increases complexity through algorithm length and look-back dependencies over int
The proliferation of Large Language Models (LLMs) in various applications necessitates a deeper understanding of their true reasoning capabilities beyond superficial performance metrics.
This research highlights a critical vulnerability in current LLM architectures, indicating that their ability to follow complex procedural instructions is not as robust as often assumed, impacting their reliability in sensitive applications.
The focus for LLM development may shift from pure benchmark accuracy to a more granular assessment of procedural execution and faithful adherence to specified algorithms.
- · AI researchers focusing on explainability and procedural robustness
- · Developers of diagnostic benchmarks and evaluation methodologies
- · Enterprises demanding verifiable LLM process adherence
- · LLMs with superficial reasoning capabilities
- · Applications relying solely on LLMs for complex, multi-step procedures without v
- · Developers prioritizing 'black box' performance over transparent execution
Increased investment in research to improve LLM procedural execution and reduce 'hallucination' of process steps.
New architectural designs for LLMs emerge that explicitly integrate procedural logic or verification mechanisms.
The development of 'algorithmic LLMs' or hybrid AI systems that combine traditional algorithms with generative capabilities for reliable task execution.
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Read at arXiv cs.CL