R0056/2026-04-01/C005 — Claim Definition¶
Claim as Received¶
Synthetic non-sycophantic training data reduces sycophancy by 4.7-10%.
Claim as Clarified¶
Synthetic non-sycophantic training data reduces sycophancy by 4.7-10%.
BLUF¶
Accurate. Wei et al. (ICLR 2024) found reductions of 4.7-10.0% across PaLM model sizes.
Scope¶
- Domain: AI safety / sycophancy research
- Timeframe: Current (as of April 2026)
- Testability: Verifiable against published research and public sources
Assessment Summary¶
Probability: Almost certain (95-99%)
Confidence: High
Hypothesis outcome: H1 prevailed.
[Full assessment in assessment.md.]
Status¶
| Field | Value |
|---|---|
| Date created | 2026-04-01 |
| Date completed | 2026-04-01 |
| Researcher profile | Phillip Moore |
| Prompt version | Unified Research Methodology v1 |
| Revisit by | 2026-10-01 |
| Revisit trigger | New evidence or corrections |