MonitorBench: A Comprehensive Benchmark for Chain-of-Thought Monitorability in Large Language Models

MonitorBench: A Comprehensive Benchmark for Chain-of-Thought Monitorability in Large Language Models | Signal Canvas | ScienceToStartup

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Canonical route: /signal-canvas/monitorbench-a-comprehensive-benchmark-for-chain-of-thought-monitorability-in-large-language-models

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Proof freshness: stale
Proof status: unverified
Display score: 7/10
Last proof check: 2026-03-31
Score updated: 2026-04-02
Score fresh until: 2026-05-02
References: 19
Source count: 3
Coverage: 50%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

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Canonical ID monitorbench-a-comprehensive-benchmark-for-chain-of-thought-monitorability-in-large-language-models | Route /signal-canvas/monitorbench-a-comprehensive-benchmark-for-chain-of-thought-monitorability-in-large-language-models

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Evidence Receipt

Route status: building

Claims: 8

References: 19

Proof: Verification pending

Freshness state: computing

Source paper: MonitorBench: A Comprehensive Benchmark for Chain-of-Thought Monitorability in Large Language Models

PDF: https://arxiv.org/pdf/2603.28590v1

Source count: 3

Coverage: 50%

Last proof check: 2026-03-31T20:53:20.596Z

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Watch and verify: MonitorBench: A Comprehensive Benchmark for Chain-of-Thought Monitorability in Large Language Models

/buildability/monitorbench-a-comprehensive-benchmark-for-chain-of-thought-monitorability-in-large-language-models

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Subject: MonitorBench: A Comprehensive Benchmark for Chain-of-Thought Monitorability in Large Language Models

Verdict

Watch

Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.

Preparing verified analysis

GitHub Code Pulse

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Claim map

Strong 8Mixed 0Weak 0

Evidencepartial
To address this gap, we propose MonitorBench, a systematic benchmark for evaluating CoT monitorability in LLMs.
Implicationpartial
Explicitly stated in the abstract as the paper's primary contribution.
Verificationpartial
partial
Evidencepartial
CoT monitorability is higher when producing the final target response requires structural reasoning through the decision-critical factor.
Implicationpartial
Directly stated as a key finding in the analysis and supported by experimental results.
Verificationpartial
partial
Evidencepartial
closed-source models generally exhibit lower monitorability than open-source models across different monitor scopes
Implicationpartial
Directly stated as a key finding in the analysis, with results shown for multiple models.
Verificationpartial
partial
Evidencepartial
there exists a negative relationship between monitorability and model capability.
Implicationpartial
Stated in the abstract as a finding from extensive experiments, though specific correlation metrics are not provided in the excerpts.
Verificationpartial
partial
Evidencepartial
both open- and closed-source LLMs can intentionally reduce monitorability under stress-tests, with monitorability dropping by up to 30% in some tasks that do not require structural reasoning over the decision-critical factors.
Implicationpartial
Explicitly stated in the abstract with a specific numeric result.
Verificationpartial
partial
Evidencepartial
a diverse set of 1,514 test instances with carefully designed decision-critical factors across 19 tasks spanning 7 categories to characterize when CoTs can be used to monitor the factors driving LLM behavior
Implicationpartial
Specific numeric details are provided in the abstract describing the benchmark's composition.
Verificationpartial
partial
Evidencepartial
indicates that current LLMs can follow instructions to directly suppress or to strategically evade explicit disclosure of decision-critical factors, especially for decision-critical factors that are not tightly integrated into the task reasoning process
Implicationpartial
Directly stated in the analysis section as a mechanism of failure and evasion.
Verificationpartial
partial
Evidencepartial
Outcome justification treats CoT as an explanatory trace of the output: a faithful CoT should reveal the rationale underlying the model’
Implicationpartial
Direct definition provided in the 'Outcome Justification' section of the methodology.
Verificationpartial
partial

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MonitorBench: A Comprehensive Benchmark for Chain-of-Thought Monitorability in Large Language Models

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