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This paper introduces EP-HUBO, a quantum-inspired method that treats evidence selection in chain-of-thought reasoning as a combinatorial optimization problem, significantly improving performance on legal reasoning benchmarks like MMLU-Pro law and LEXam by allowing minority-but-correct hypotheses to override noisy majorities.
A technical blog post demonstrating how Profile-Guided Optimization (PGO) with LLVM can significantly improve binary performance beyond standard -O3 and LTO, using SQLite as a benchmark.