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R0057/2026-04-01/C006 — Assessment

BLUF

Confirmed. All six named alternatives are well-documented: DPO (2023), KTO (2024), GRPO (2024), Constitutional AI (2022), ORPO (2024), and RLVR (2024-2025). All are widely adopted or cited.

Probability

Rating: Almost certain (95-99%)

Confidence in assessment: High

Confidence rationale: These are all well-established in the ML literature with multiple implementations and adoption by major labs.

Reasoning Chain

  1. All six alternatives are documented across multiple technical surveys. DPO eliminates the reward model. KTO uses binary feedback. GRPO uses group-relative advantages. Constitutional AI uses principle-based feedback. ORPO combines SFT and preference optimization. RLVR uses programmatic verifiers. [SRC01-E01, High reliability, High relevance]

  2. JUDGMENT: Confirmed. All six named alternatives are well-documented: DPO (2023), KTO (2024), GRPO (2024), Constitutional AI (2022), ORPO (2024), and RLVR (2024-2025). All are widely adopted or cited.

Evidence Base Summary

Source Description Reliability Relevance Key Finding
SRC01 Multiple survey articles on RLHF alternatives High High All six named alternatives (DPO, KTO, GRPO, Constitutional AI, ORPO, RLVR) are documented in the literature

Collection Synthesis

Dimension Assessment
Evidence quality High
Source agreement High
Source independence Medium
Outliers None identified

Detail

The evidence supports the assessment. These are all well-established in the ML literature with multiple implementations and adoption by major labs.

Gaps

Missing Evidence Impact on Assessment
Additional independent verification Would strengthen confidence

Researcher Bias Check

Declared biases: Anti-sycophancy bias could influence interpretation toward confirming sycophancy claims.

Influence assessment: Mitigated by reliance on peer-reviewed and primary sources.

Cross-References

Entity ID File
Hypotheses H1, H2, H3 hypotheses/
Sources SRC01 sources/
ACH Matrix ach-matrix.md
Self-Audit self-audit.md