Information-Directed Hypothesis Selection

Principle-Evolvable Scientific Discovery via Uncertainty Minimization

arXiv:2602.06448v2 Announce Type: replace Abstract: Large Language Model (LLM)-based scientific agents have accelerated scientific discovery, yet they often suffer from significant inefficiencies due to adherence to fixed initial priors. Existing approaches predominantly operate within a static hypothesis space, which restricts the discovery of novel phenomena, resulting in computational waste when baseline theories fail. To address this, we propose shifting the focus from searching...