2 citations · 2 across the 6 of their papers we have counts for
6 papers
Scalably computing metric magnitude
Steve Huntsman, Jewell Thomas, Cynthia Ukawu
Applications of metric magnitude often rely on numerically exact results in order to exploit a connection with information theory. We examine various approaches for scaling the den…
Automatic coherence-driven inference on arguments
Steve Huntsman
Inconsistencies are ubiquitous in law, administration, and jurisprudence. Though a cure is too much to hope for, we propose a technological remedy. Large language models (LLMs) can…
Coherence-driven inference for cybersecurity
Steve Huntsman
Large language models (LLMs) can compile weighted graphs on natural language data to enable automatic coherence-driven inference (CDI) relevant to red and blue team operations in c…
Benchmarking graph construction by large language models for coherence-driven inference
Steve Huntsman, Jewell Thomas
We devise an algorithm to generate propositions that objectively instantiate graphs supporting coherence-driven inference. We also benchmark the ability of large language models (L…
Prospects for inconsistency detection using large language models and sheaves
Steve Huntsman, Michael Robinson, Ludmilla Huntsman
We demonstrate that large language models can produce reasonable numerical ratings of the logical consistency of claims. We also outline a mathematical approach based on sheaf theo…
Greybox fuzzing time-intensive programs
Steve Huntsman
We examine (directed) greybox fuzzing from a geometrical perspective, viewing dissimilarities on inputs and on control flow graphs (with dynamical statistics) as primitive objects…