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In recent months, Language Models (LMs) have become a part of dailydiscourse, with focus on OpenAI and the potential of Artificial GeneralIntelligence (AGI). Furthermore, the leaking of LLama's weights to the publichas led to an influx of innovations demonstrating the impressive capabilitiesof generative LMs. While we believe that AGI is still a distant goal, werecognize the potential of LMs in solving tasks such as searching complexdocuments, compiling reports with basic analysis, and providing assistance inproblem-solving. In this paper, we propose formalizing the execution model oflanguage models. We investigate current execution models, to find that thisformalism has received little attention, and present our contribution: thefirst formalized execution model for LMs. We introduce a new algorithm forsampling the predictions of LMs, which we use to build a reliable andinspectable execution model. We introduce a low-level language to write"cognitive program" for this execution model. We hope to shed light on the needfor execution models for LMs and encourage further research in this area.

Structured Thoughts Automaton: First Formalized Execution Model for Auto-Regressive Language Models