Dataset-level metrics in diffusion language models mask substantial sample-level non-determinism that varies with model and system factors, which a new Factor Variance Attribution metric can decompose.
Assessing consistency and reproducibility in the outputs of large language models: Evidence across diverse finance and accounting tasks
4 Pith papers cite this work. Polarity classification is still indexing.
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Entropy minimization on self-generated outputs elicits strong reasoning in pretrained LLMs, matching or exceeding supervised RL methods on benchmarks.
Financial AI systems using tabular models, graph networks, and LLM agents exhibit nondeterminism that undermines reproducibility, quantified via experiments on public datasets and addressed by a proposed layered evaluation framework linking metrics to audit readiness.
Shapley values for LLM explanations in financial text are shown via theory and experiments to produce attributions consistent with financial reasoning.
citing papers explorer
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Dataset-Level Metrics Attenuate Non-Determinism: A Fine-Grained Non-Determinism Evaluation in Diffusion Language Models
Dataset-level metrics in diffusion language models mask substantial sample-level non-determinism that varies with model and system factors, which a new Factor Variance Attribution metric can decompose.
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The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
Entropy minimization on self-generated outputs elicits strong reasoning in pretrained LLMs, matching or exceeding supervised RL methods on benchmarks.
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From Accuracy to Auditability: A Survey of Determinism in Financial AI Systems
Financial AI systems using tabular models, graph networks, and LLM agents exhibit nondeterminism that undermines reproducibility, quantified via experiments on public datasets and addressed by a proposed layered evaluation framework linking metrics to audit readiness.
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Shapley in Context: Explaining Financial Language with Domain Expertise
Shapley values for LLM explanations in financial text are shown via theory and experiments to produce attributions consistent with financial reasoning.