Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!

View PDF HTML (experimental) Abstract:Intermediate token generation (ITG), where a model produces output before the solution, has become a standard method to improve the performance of language models on reasoning tasks. These intermediate tokens have been called \say{reasoning traces} or even \say{thinking traces} -- implicitly anthropomorphizing the traces, and implying that these traces resemble steps a human might take when solving a challenging problem, and as such can provide an interpretable window into the operation of the model's thinking process to the end user. In this position paper, we present evidence that this anthropomorphization isn't a harmless metaphor, and instead is quite dangerous -- it confuses the nature of these models and how to use them effectively, and leads to questionable research. We call on the community to avoid such anthropomorphization of intermediate tokens. Comments: Appears in ICML 2026. [This is a fork of v1. This fork, while overlapping with v1 in background section, differs both in the overall focus as well as the specific argument against anthropomorphization of reasoning traces] Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2504.09762 [cs.AI] (or arXiv:2504.09762v4 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2504.09762 arXiv-issued DOI via DataCite Journal reference: ICML 2026 Submission history From: Subbarao Kambhampati [view email] [v1] Mon, 14 Apr 2025 00:03:34 UTC (381 KB) [v2] Tue, 27 May 2025 16:35:47 UTC (536 KB) [v3] Fri, 6 Mar 2026 14:36:07 UTC (1,321 KB) [v4] Tue, 9 Jun 2026 20:08:39 UTC (4,278 KB)