Scalable agent alignment via reward modeling: a research direction
by DeepMind · free · Last verified 2026-03-17
Outlines a research direction for scalable AI alignment through recursive reward modeling, where AI assistance enables humans to evaluate complex AI behaviors they could not assess directly. The paper discusses debate, amplification, and recursive reward modeling as complementary approaches to aligning increasingly capable AI systems.
https://arxiv.org/abs/1811.07871 ↗B
B—Above Average
Adoption: B+Quality: AFreshness: C+Citations: AEngagement: F
Specifications
- License
- Open Access
- Pricing
- free
- Capabilities
- reward-modeling, scalable-oversight, human-ai-collaboration, alignment
- Integrations
- Use Cases
- ai-safety-research, alignment-methodology, research
- API Available
- No
- Tags
- alignment, scalable-oversight, reward-modeling, recursive, debate
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
67.9Adoption
72
Quality
88
Freshness
50
Citations
86
Engagement
0
Put AI to work for your business
Deploy this paper alongside autonomous AaaS agents that handle tasks end-to-end — no babysitting required.