Cognitive BASIC: An In-Model Interpreted Reasoning Language for LLMs
On the map: LLM reasoning → Prompting and chain-of-thought reasoning
Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Prompting and chain-of-thought reasoning, one of 17 directions in LLM reasoning. Builds on 5 of its 8 references that are in the map. First posted on arXiv 20 Nov 2025.
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- 2024Unlocking Structured Thinking in Language Models with Cognitive Prompting3 Oct
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Models28 Jan
Other references · 3
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
- 2023MemGPT: Towards LLMs as Operating Systemscited by 1,389
- 2023OpenCog Hyperon: A Framework for AGI at the Human Level and Beyondcited by 9
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- 2024LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models
- 2026Evaluating Prompting and Execution-Based Methods for Deterministic Computation in LLMs
- 2026Exploring Extrinsic and Intrinsic Properties for Effective Reasoning with Code Interpreter
- 2023ART: Automatic multi-step reasoning and tool-use for large language models
- 2025Mapping the Minds of LLMs: A Graph-Based Analysis of Reasoning LLM
- 2025IAO Prompting: Making Knowledge Flow Explicit in LLMs through Structured Reasoning Templates
- 2025Cognitive Foundations for Reasoning and Their Manifestation in LLMs
- 2026The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes