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‪Adam Gleave‬ - ‪Google Scholar‬

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Credibility Rating

4/5
High(4)

High quality. Established institution or organization with editorial oversight and accountability.

Rating inherited from publication venue: Google Scholar

Adam Gleave is a key AI safety researcher at FAR.AI whose work on adversarial policies, reward modeling, and imitation learning is frequently cited in the alignment and technical safety literature.

Metadata

Importance: 52/100homepage

Summary

Google Scholar profile for Adam Gleave, an AI safety researcher affiliated with FAR.AI, with 7,467 citations and an h-index of 20. His research spans inverse reinforcement learning, reward modeling, adversarial policies, and AI safety evaluation. He collaborates with prominent researchers including Stuart Russell, Sergey Levine, and Kellin Pelrine.

Key Points

  • 7,467 total citations with h-index of 20, indicating significant research impact in AI safety and reinforcement learning
  • Co-founder/researcher at FAR.AI, a nonprofit focused on AI safety research
  • Research focuses on reward learning, adversarial policies, and evaluation of AI systems
  • Collaborates with Stuart Russell (UC Berkeley), Sergey Levine, and other leading AI safety researchers
  • Citation growth has accelerated sharply since 2021, reflecting increasing relevance of his research areas

Cited by 1 page

PageTypeQuality
FAR AIOrganization76.0

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Resource ID: 361c8351f362da8d | Stable ID: sid_79LVshVE0I