aiqbench analysis
This position paper argues that labeling intermediate tokens as "reasoning traces" is a dangerous anthropomorphism that obscures the actual mechanics of language models and compromises research validity. By rejecting the metaphor that these tokens represent human-like thinking steps, the authors urge the community to avoid misleading interpretations of model outputs. This distinction is critical for researchers aiming to accurately assess model capabilities and prevent flawed conclusions in future studies.
Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!
arXiv:2504.09762v4 Announce Type: replace 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.
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.
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]
Artificial Intelligence (cs.AI)
arXiv:2504.09762 [cs.AI]
(or arXiv:2504.09762v4 [cs.AI] for this version)
Full text under the publisher's open licence · 177 words
