C008 — Claim Definition¶


Research	R0055 — RLHF Yes-Men Claims
Run	2026-04-01
Claim	C008

Claim as Received¶

RLVR (Reinforcement Learning with Verifiable Rewards) replaces human preference signals with deterministic correctness verification

Claim as Clarified¶

RLVR (Reinforcement Learning with Verifiable Rewards) replaces human preference signals with deterministic correctness verification

BLUF¶

Accurate. RLVR uses programmatic verifiers returning binary correct/incorrect signals (1.0/0.0) instead of learned reward models based on human preferences. This is well-documented across multiple sources.

Scope¶

Domain: AI alignment, sycophancy, enterprise AI
Timeframe: 2022-2026
Testability: Verifiable against published research and documentation

Assessment Summary¶

Probability: Almost certain (95-99%)

Confidence: High

Hypothesis outcome: H1 prevails — see assessment for details.

[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	Evolution of RLVR to include non-binary reward signals