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Toward Generalist Autonomous Research via Hypothesis-Tree Refinement
Arbor is an AI framework where a long-running coordinator directs short-lived worker agents to run experiments, track results in a tree structure, and iteratively improve research artifacts—without human supervision. It outperformed Codex and Claude Code on six real research tasks.
▾ Why it matters
Autonomous research agents that compound learnings over time directly address the core bottleneck in AI-assisted R&D: context and strategy loss between iterations. This architecture pattern is a blueprint for commercial AI research automation in drug discovery, ML engineering, and data pipelines.
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