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No memory substrate is a one-size-fits-all solution; the right choice depends on the task, with broad retrieval boosting QA but hindering decision-making.
A-SR achieves nearly a doubling of accuracy in symbolic regression tasks, showcasing a transformative approach to LLM-guided formula discovery.
Current LLM-driven theorem provers fall short in addressing the complexities of frontier mathematics, necessitating a shift towards research agents that can engage in rigorous mathematical exploration.
