Can A Cognitive Architecture Fundamentally Enhance LLMs? Or Vice Versa?
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Abstract (arXiv)
The paper discusses what is needed to address the limitations of current LLM-centered AI systems. The paper argues that incorporating insights from human cognition and psychology, as embodied by a computational cognitive architecture, can help develop systems that are more capable, more reliable, and more human-like. It emphasizes the importance of the dual-process architecture and the hybrid neuro-symbolic approach in addressing the limitations of current LLMs. In the opposite direction, the paper also highlights the need for an overhaul of computational cognitive architectures to better reflect advances in AI and computing technology. Overall, the paper advocates for a multidisciplinary, mutually beneficial approach towards developing better models both for AI and for understanding the human mind.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jan 2024.
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Citing papers per year: 2024: 4; 2025: 5.
9 papers.
- 2024Prompting Techniques for Reducing Social Bias in LLMs through System 1 and System 2 Cognitive Processescited by 38
- 2024Towards Rationality in Language and Multimodal Agents: A Surveycited by 15
- 2025CAIM: Development and Evaluation of a Cognitive AI Memory Framework for Long-Term Interaction with Intelligent Agentscited by 7
- 2024Psychology of Artificial Intelligence: Epistemological Markers of the Cognitive Analysis of Neural Networkscited by 5
- 2024Analyzing the Roles of Language and Vision in Learning from Limited Datacited by 2
- 2025Computational Multi-Agents Society Experiments: Social Modeling Framework Based on Generative Agentscited by 2
- 2025TRIZ Agents: A Multi-Agent LLM Approach for TRIZ-Based Innovationcited by 1
- 2025Automated stereotactic radiosurgery planning using a human-in-the-loop reasoning large language model agentcited by 1
- 2025Polysemy of Synthetic Neurons Towards a New Type of Explanatory Categorical Vector Spacescited by 0
- 2025Automated stereotactic radiosurgery planning using a human-in-the-loop reasoning large language model agent23 Dec 2025
- 2025Computational Multi-Agents Society Experiments: Social Modeling Framework Based on Generative Agents24 Aug 2025
- 2025TRIZ Agents: A Multi-Agent LLM Approach for TRIZ-Based Innovation23 Jun 2025
- 2025CAIM: Development and Evaluation of a Cognitive AI Memory Framework for Long-Term Interaction with Intelligent Agents19 May 2025
- 2025Polysemy of Synthetic Neurons Towards a New Type of Explanatory Categorical Vector Spaces30 Apr 2025
- 2024Psychology of Artificial Intelligence: Epistemological Markers of the Cognitive Analysis of Neural Networks4 Jul 2024
- 2024Towards Rationality in Language and Multimodal Agents: A Survey1 Jun 2024
- 2024Prompting Techniques for Reducing Social Bias in LLMs through System 1 and System 2 Cognitive Processes26 Apr 2024
- 2024Analyzing the Roles of Language and Vision in Learning from Limited Data15 Feb 2024