A step toward recursive self-improvement with human feedback (RSIHF): ten AI agents develop models, people judge their outputs, and those judgments inform the next round of development, alongside capability and safety evaluations.
Research agents can obtain high scores without making real improvements. We examine when AI reviewers catch these shortcuts and whether agents can use review feedback to conceal them.