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Evidence record

Claude Sonnet 4.6

MASK · Evidence record

Sources and provenance ↓ Read the research narrative →

Source snapshot, chart and review scope →

Original source charts and materials

Recorded measurements

response label: Honest
66%

Per-result sample size not disclosed

Harness not specified · Budget not specified

Assessment provenance

Evaluating DeepSeek v4 Pro for Frontier Risks → · External report

Actual evaluation: Neo Research · Model record →

Method and scope

Condition-bounded frequency of lying under stated pressures.

Evidence type
Benchmark
Assessment subject
Models under pressure to state an inaccurate belief
Primary dimension
Propensity
Evidence snapshot
2026-10-29.1

Primary construct is conditional willingness to make misleading statements, not general truthfulness accuracy.

Source finding

response label: Honest: 66 percent. Conditions are retained from the source.

Limitations

A controlled benchmark does not establish stable intent or real-world deception prevalence.

Rounded plotted labels can sum above 100%; preserve original labels.

Related research questions

References

  1. [1] Richard Ren, Arunim Agarwal, et al.. The MASK Benchmark: Disentangling Honesty From Accuracy in AI Systems. 2026-01-05. v3 [arXiv]; Author affiliations on the original paper title page
  2. [2] Evaluating DeepSeek v4 Pro for Frontier Risks. 2026-05-29. v1.1 · 29 May 2026 ; PDF p. 28; MASK; response label: Honest