R0057/2026-04-01/C005/SRC01

Research	R0057 — RLHF Yes-Men Claims v3
Run	2026-04-01
Claim	C005
Search	S01
Result	S01-R01
Source	SRC01

Wei et al. (2023) — Simple synthetic data reduces sycophancy

Source

Field	Value
Title	Simple synthetic data reduces sycophancy in large language models
Publisher	arXiv / ICLR 2024
Author(s)	Jerry Wei, Da Huang, Yifeng Lu, Denny Zhou, Quoc V. Le
Date	2024-2026
URL	https://arxiv.org/abs/2308.03958
Type	Research paper

Summary

Dimension	Rating
Reliability	High
Relevance	High
Bias: Missing data	Low risk
Bias: Measurement	Low risk
Bias: Selective reporting	Low risk
Bias: Randomization	N/A — not an RCT
Bias: Protocol deviation	N/A — not an RCT
Bias: COI/Funding	Low risk

Rationale

Dimension	Rationale
Reliability	Research paper from established institution/publication
Relevance	Directly addresses the claim under investigation
Bias flags	No significant bias concerns identified

Evidence Extracts

Evidence ID	Summary
SRC01-E01	Synthetic data reduces sycophancy by 4.7% to 10.0% across PaLM model variants