Repository for the paper "Auditing Pay-Per-Token in Large Language Models", AISTATS'26
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Updated
Mar 23, 2026 - Jupyter Notebook
Repository for the paper "Auditing Pay-Per-Token in Large Language Models", AISTATS'26
A kernel-userland protocol enforcing information-theoretic bounds on AI adaptivity leakage, benchmark gaming, and capability spillover.
This repository contains the code for the paper "Optimizing Social Utility in Sequential Experiments".
Benchmark for statistically valid AI scientist systems, using audit-closed protocols, transparency logs, and sequential inference to prevent false discoveries in autonomous research agents.
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