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

Fuente: arXiv
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Hauptverfasser: Kambhampati, Subbarao, Valmeekam, Karthik, Bhambri, Siddhant, Palod, Vardhan, Saldyt, Lucas, Stechly, Kaya, Samineni, Soumya Rani, Kalwar, Durgesh, Biswas, Upasana
Format: Preprint
Veröffentlicht: 2025
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author Kambhampati, Subbarao
Valmeekam, Karthik
Bhambri, Siddhant
Palod, Vardhan
Saldyt, Lucas
Stechly, Kaya
Samineni, Soumya Rani
Kalwar, Durgesh
Biswas, Upasana
author_facet Kambhampati, Subbarao
Valmeekam, Karthik
Bhambri, Siddhant
Palod, Vardhan
Saldyt, Lucas
Stechly, Kaya
Samineni, Soumya Rani
Kalwar, Durgesh
Biswas, Upasana
contents 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{thoughts} -- 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.
format Preprint
id arxiv_https___arxiv_org_abs_2504_09762
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!
Kambhampati, Subbarao
Valmeekam, Karthik
Bhambri, Siddhant
Palod, Vardhan
Saldyt, Lucas
Stechly, Kaya
Samineni, Soumya Rani
Kalwar, Durgesh
Biswas, Upasana
Artificial Intelligence
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{thoughts} -- 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.
title Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!
topic Artificial Intelligence
url https://arxiv.org/abs/2504.09762