Recognition: unknown
Impact of Task Phrasing on Presumptions in Large Language Models
Pith reviewed 2026-05-09 19:09 UTC · model grok-4.3
The pith
Task phrasing induces presumptions in LLMs that persist even when they provide reasoning steps.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
LLMs are susceptible to presumptions when making decisions even with reasoning steps, but neutral task phrasing enables logical reasoning without much presumptions.
What carries the argument
The iterated prisoner's dilemma as a case study to measure how different task phrasings affect LLM decisions and reasoning.
If this is right
- Proper task phrasing reduces the risk of presumptions affecting LLM outputs.
- LLMs may not adapt well to task deviations if phrasing creates strong initial assumptions.
- Reasoning chains in LLMs do not automatically override phrasing-induced biases.
- Neutral prompts promote more reliable decision-making in LLMs.
Where Pith is reading between the lines
- Prompt designers should prioritize neutral language to minimize unintended biases in LLM applications.
- Similar presumption effects could occur in other interactive or game-based tasks beyond the prisoner's dilemma.
- Testing across multiple LLMs and tasks would strengthen understanding of this vulnerability.
Load-bearing premise
The iterated prisoner's dilemma is a suitable case study for how presumptions from task phrasing affect LLM performance in unpredictable real-world applications.
What would settle it
Finding that LLMs still exhibit presumptions under neutral phrasing or show no difference between phrasings in the prisoner's dilemma experiments would challenge the central claim.
read the original abstract
Concerns with the safety and reliability of applying large-language models (LLMs) in unpredictable real-world applications motivate this study, which examines how task phrasing can lead to presumptions in LLMs, making it difficult for them to adapt when the task deviates from these assumptions. We investigated the impact of these presumptions on the performance of LLMs using the iterated prisoner's dilemma as a case study. Our experiments reveal that LLMs are susceptible to presumptions when making decisions even with reasoning steps. However, when the task phrasing was neutral, the models demonstrated logical reasoning without much presumptions. These findings highlight the importance of proper task phrasing to reduce the risk of presumptions in LLMs.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper examines how task phrasing influences presumptions in LLMs, using the iterated prisoner's dilemma as a case study. It reports that LLMs exhibit presumptions in decision-making even with reasoning steps, but neutral task phrasing enables logical reasoning with reduced presumptions. This is presented as relevant for improving safety and reliability in real-world LLM applications.
Significance. If substantiated with quantitative evidence, the work could inform prompt engineering practices by showing that neutral phrasing reduces unintended assumptions in LLM outputs. The structured IPD setup allows controlled testing of decision-making, providing a concrete example of phrasing effects, though broader applicability to open-ended tasks would strengthen its relevance.
major comments (2)
- [§3 (Experimental Setup)] §3 (Experimental Setup): The manuscript provides no quantitative metrics, measurement criteria for 'presumptions', model specifications (e.g., which LLMs, temperature settings), or statistical analysis to support the claims that LLMs are 'susceptible to presumptions' or that neutral phrasing reduces them; without these, the experimental findings cannot be evaluated.
- [§1 (Introduction)] §1 (Introduction): The motivation linking results to safety in 'unpredictable real-world applications' is not supported by the IPD case study, which uses a fixed payoff matrix, perfect information, and repeated discrete choices; no evidence, controls, or discussion addresses whether presumption mechanisms (e.g., assuming cooperation) transfer to ambiguous, open-ended domains.
minor comments (1)
- [Abstract] Abstract: Summarizes findings without any quantitative results or details on models/experiments, which reduces clarity for readers expecting empirical grounding.
Simulated Author's Rebuttal
We thank the referee for the valuable comments, which help us improve the manuscript. Below we provide point-by-point responses to the major comments.
read point-by-point responses
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Referee: [§3 (Experimental Setup)] §3 (Experimental Setup): The manuscript provides no quantitative metrics, measurement criteria for 'presumptions', model specifications (e.g., which LLMs, temperature settings), or statistical analysis to support the claims that LLMs are 'susceptible to presumptions' or that neutral phrasing reduces them; without these, the experimental findings cannot be evaluated.
Authors: We concur that the Experimental Setup section lacks sufficient quantitative support and details. We will revise it to include quantitative metrics (such as cooperation rates under different phrasings), explicit criteria for identifying presumptions (deviations from rational play in the IPD), model specifications, temperature settings, and statistical analyses to substantiate the susceptibility claims and the benefits of neutral phrasing. revision: yes
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Referee: [§1 (Introduction)] §1 (Introduction): The motivation linking results to safety in 'unpredictable real-world applications' is not supported by the IPD case study, which uses a fixed payoff matrix, perfect information, and repeated discrete choices; no evidence, controls, or discussion addresses whether presumption mechanisms (e.g., assuming cooperation) transfer to ambiguous, open-ended domains.
Authors: We agree that the IPD case study is structured and does not provide direct evidence or controls for transfer to open-ended domains. While the introduction uses the results to motivate safety considerations, we will revise the introduction and add a dedicated limitations section to clarify the scope of the findings, discuss potential implications for real-world applications with appropriate caveats, and suggest directions for future research on more ambiguous tasks. revision: partial
- Empirical evidence or controls showing that the presumption mechanisms observed in the IPD transfer to ambiguous, open-ended real-world domains.
Circularity Check
No circularity: purely empirical study with no derivations or self-referential logic.
full rationale
The paper reports experimental observations on LLMs in the iterated prisoner's dilemma under varying task phrasings. No equations, fitted parameters, predictions derived from inputs, or load-bearing self-citations appear in the abstract or described structure. Claims rest on direct experimental outcomes rather than any chain that reduces to its own definitions or prior author work by construction. This is a standard non-circular empirical report.
Axiom & Free-Parameter Ledger
Reference graph
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discussion (0)
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