Cognitive BASIC: An In-Model Interpreted Reasoning Language for LLMs

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Kramer, Oliver
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866908668448997376
author Kramer, Oliver
author_facet Kramer, Oliver
contents Cognitive BASIC is a minimal, BASIC-style prompting language and in-model interpreter that structures large language model (LLM) reasoning into explicit, stepwise execution traces. Inspired by the simplicity of retro BASIC, we repurpose numbered lines and simple commands as an interpretable cognitive control layer. Modern LLMs can reliably simulate such short programs, enabling transparent multi-step reasoning inside the model. A natural-language interpreter file specifies command semantics, memory updates, and logging behavior. Our mental-model interpreter extracts declarative and procedural knowledge, detects contradictions, and produces resolutions when necessary. A comparison across three LLMs on a benchmark of knowledge extraction, conflict detection, and reasoning tasks shows that all models can execute Cognitive BASIC programs, with overall strong but not uniform performance.
format Preprint
id arxiv_https___arxiv_org_abs_2511_16837
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Cognitive BASIC: An In-Model Interpreted Reasoning Language for LLMs
Kramer, Oliver
Artificial Intelligence
Computation and Language
Cognitive BASIC is a minimal, BASIC-style prompting language and in-model interpreter that structures large language model (LLM) reasoning into explicit, stepwise execution traces. Inspired by the simplicity of retro BASIC, we repurpose numbered lines and simple commands as an interpretable cognitive control layer. Modern LLMs can reliably simulate such short programs, enabling transparent multi-step reasoning inside the model. A natural-language interpreter file specifies command semantics, memory updates, and logging behavior. Our mental-model interpreter extracts declarative and procedural knowledge, detects contradictions, and produces resolutions when necessary. A comparison across three LLMs on a benchmark of knowledge extraction, conflict detection, and reasoning tasks shows that all models can execute Cognitive BASIC programs, with overall strong but not uniform performance.
title Cognitive BASIC: An In-Model Interpreted Reasoning Language for LLMs
topic Artificial Intelligence
Computation and Language
url https://arxiv.org/abs/2511.16837