Process Supervision
process-supervisionapproachPath: /knowledge-base/responses/process-supervision/
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"summary": "Process supervision trains AI to show correct reasoning steps rather than just final answers, achieving 15-25% absolute improvements on math benchmarks while making reasoning auditable. However, it shares RLHF's fundamental limitation: humans cannot verify superhuman reasoning steps, and models might maintain separate internal reasoning from visible chains.",
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Backlinks (12)
| id | title | type | relationship |
|---|---|---|---|
| why-alignment-hard | Why Alignment Might Be Hard | argument | — |
| alignment-robustness-trajectory | Alignment Robustness Trajectory | analysis | — |
| jan-leike | Jan Leike | person | — |
| paul-christiano | Paul Christiano | person | — |
| alignment-training-overview | Training Methods (Overview) | concept | — |
| capability-elicitation | Capability Elicitation | approach | — |
| debate | AI Safety via Debate | approach | — |
| mech-interp | Mechanistic Interpretability | research-area | — |
| reward-modeling | Reward Modeling | approach | — |
| scalable-oversight | Scalable Oversight | research-area | — |
| weak-to-strong | Weak-to-Strong Generalization | approach | — |
| distributional-shift | AI Distributional Shift | risk | — |