Reasoning models & chain of thought
Publication dates and source age
Sources counted: 4
Newest dated source: 2025-07-15
At least one source was published within the 18-month window.
Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.
Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.
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In plain language
Models trained or configured to work through intermediate steps before giving a final answer. [1]
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Limits & distinctions
A readable reasoning trace can help with monitoring, but it is an incomplete account of the model's internal calculations. More steps do not by themselves prove the answer correct. [3] [4]
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A fuller explanation
These systems can spend additional computation generating steps, checking attempts or exploring alternatives. DeepSeek-R1 is one researched example of using reinforcement learning to encourage such behavior. A written sequence of intermediate steps is often called a chain of thought. [1]
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How it relates to the map
Check results on relevant tasks and how much time or computation those results required. [1] [2]
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https://theaiatlas.org/ideas/reasoning-models/
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Sources and what we read
1. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Source is over 18 months old.
Publication dates and source age
Sources counted: 1
Newest dated source: 2025-01-22
Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.
Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.
Read abstract, introduction and chain-of-thought/inference-time-compute discussion. Dates checked against the abstract page's version history. Used for training and extended reasoning examples; the authors' benchmark results are not a universal ranking or an explanation of all model internals.
2. Holistic Evaluation of Language Models
Source is over 18 months old.
Publication dates and source age
Sources counted: 1
Newest dated source: 2022-11-16
Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.
Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.
Read the abstract and version history, including multiple use cases and metrics, standardized comparisons and acknowledged coverage gaps. Used for evaluation principles; historical model scores are not presented as current rankings.
3. Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety
Publication dates and source age
Sources counted: 1
Newest dated source: 2025-07-15
At least one source was published within the 18-month window.
Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.
Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.
Read abstract, rationale, research questions, limitations and conclusion. A research position paper: reasoning traces may add monitoring value while remaining incomplete and potentially fragile. Authors' views are not necessarily their institutions' positions; cited experiments were not all independently reviewed.
4. Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile
Source is over 18 months old.
Publication dates and source age
Sources counted: 1
Newest dated source: 2024-07
Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.
Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.
Read introduction, section 2.2 on confabulation, and selected MEASURE actions 2.3, 2.5, 2.6, 2.7 and 2.9 concerning evaluation evidence, generalization, citations, generated-code review and safeguards. A voluntary risk-management profile; no claim that all 64 pages or every referenced study was reviewed.
Edition and machine-readable evidence
Content version 0.20.0. Evidence cutoff 2026-09-15; this does not mean every source was read on that day.
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