Vertex-Softmax computes the tightest sound bounds on softmax from pre-softmax score intervals alone via vertex optimization with log-linear complexity and is proven optimal for interval-only information.
arXiv preprint arXiv:2406.09714 , year=
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The paper introduces an optimization framework for AI agents to strategically seek support, proving a threshold policy on support value and providing an online algorithm to control missed-support error without distributional assumptions.
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Vertex-Softmax computes the tightest sound bounds on softmax from pre-softmax score intervals alone via vertex optimization with log-linear complexity and is proven optimal for interval-only information.
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Unsupervised single-generation confidence calibration for reasoning LLMs via offline self-consistency proxy distillation outperforms baselines on math and QA tasks and improves selective prediction.
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