Toward Generalist Autonomous Research via Hypothesis-Tree Refinement
Researchers have developed Arbor, a novel AI framework designed for autonomous scientific research. Arbor utilizes a persistent knowledge tree called Hypothesis Tree Refinement (HTR) to link hypotheses, evidence, and insights, enabling cumulative learning across long-term projects. In evaluations across six research tasks, Arbor outperformed Codex and Claude Code, achieving over 2.5 times their average relative gain and reaching 86.36% Any Medal on MLE-Bench Lite with GPT-5.5. AI
IMPACT Arbor's approach to cumulative learning and autonomous optimization could accelerate scientific discovery and development across various AI-related fields.