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Algebraic integral points on arithmetic surfaces exhibit predictable limit distributions, revealing a deep connection between Galois orbits and local probability measures.
OaK transforms LLM agents by grounding their decision-making processes in dynamically constructed ontologies, leading to enhanced reliability in multi-step reasoning.
AgenticDataBench reveals that LLM-based data agents can be rigorously evaluated across diverse real-world scenarios, highlighting their strengths and weaknesses in handling complex data tasks.
