Computer Science

The Illusion of the Illusion of Thinking

C. Opus and A. Lawson

Discover the intriguing findings by Shojaee et al. (2025), who reveal that Large Reasoning Models may experience 'accuracy collapse' under complex planning puzzles. This research, conducted by C. Opus and A. Lawson, challenges the prevailing narrative by suggesting that these anomalies are more about experimental design than actual reasoning failures. Dive into the details!

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Abstract

Shojaee et al. (2025) report that Large Reasoning Models (LRMs) exhibit "accuracy collapse" on planning puzzles beyond certain complexity thresholds. This paper argues that these findings primarily reflect experimental design limitations rather than fundamental reasoning failures. Three issues are identified: (1) exceeding model output token limits, (2) automated evaluation failing to distinguish reasoning failures from practical constraints, and (3) the inclusion of mathematically impossible puzzle instances. Controlling for these artifacts shows high accuracy on previously reported failures.

Publisher

arXiv

Published On

Jun 10, 2025

Authors

C. Opus, A. Lawson

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