mlsanityData to 13 Oct 2026

Exploiting Language Models as a Source of Knowledge for Cognitive Agents

arXiv 2310.06846 ↗First posted 5 Sep 2023cs.AI cs.CLcited by 15

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

Large language models (LLMs) provide capabilities far beyond sentence completion, including question answering, summarization, and natural-language inference. While many of these capabilities have potential application to cognitive systems, our research is exploiting language models as a source of task knowledge for cognitive agents, that is, agents realized via a cognitive architecture. We identify challenges and opportunities for using language models as an external knowledge source for cognitive systems and possible ways to improve the effectiveness of knowledge extraction by integrating extraction with cognitive architecture capabilities, highlighting with examples from our recent work in this area.

Key facts. Cited by 15 papers in the map (data through 13 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 19 of its 47 references that are in the map. First posted on arXiv 5 Sep 2023.

Builds on

19 of 47 references.

References · 19

  1. 2020Language Models are Few-Shot Learnerscited by 32,320
  2. 2023GPT-4 Technical Reportcited by 18,278
  3. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,657
  4. 2021Program Synthesis with Large Language Modelscited by 3,573
  5. 2023RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Controlcited by 3,022
  6. 2023PaLM-E: An Embodied Multimodal Language Modelcited by 2,052
  7. 2019Language Models as Knowledge Bases?cited by 1,931
  8. 2016ConceptNet 5.5: An Open Multilingual Graph of General Knowledgecited by 1,065
  9. 2021Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigmcited by 605
  10. 2019COMET: Commonsense Transformers for Automatic Knowledge Graph Constructioncited by 450
  11. 2023Language Models can Solve Computer Taskscited by 371
  12. 2023TidyBot: Personalized Robot Assistance with Large Language Modelscited by 220
7 more
  1. 2023On the Planning Abilities of Large Language Models (A Critical Investigation with a Proposed Benchmark)cited by 85
  2. 2021GPT3-to-plan: Extracting plans from text using GPT-3cited by 26
  3. 2022Few-shot Subgoal Planning with Language Modelscited by 22
  4. 2023Getting from Generative AI to Trustworthy AI: What LLMs might learn from Cyccited by 19
  5. 2021Language Models as a Knowledge Source for Cognitive Agentscited by 7
  6. 2022Integrating Diverse Knowledge Sources for Online One-shot Learning of Novel Taskscited by 6
  7. 2022Improving Language Model Prompting in Support of Semi-autonomous Task Learningcited by 6

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Cited by year (2026 to 13 Oct)

Citing papers per year: 2024: 6; 2025: 8; 2026: 1.

15 papers.

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  1. 2024Large Language Models and Cognitive Science: A Comprehensive Review of Similarities, Differences, and Challengescited by 49
  2. 2024On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)cited by 40
  3. 2025Neuro-Symbolic AI in 2024: A Systematic Reviewcited by 37
  4. 2024Large Language Model Benchmarks in Medical Taskscited by 17
  5. 2025Probing a Vision-Language-Action Model for Symbolic States and Integration into a Cognitive Architecturecited by 16
  6. 2025Waking Up an AI: A Quantitative Framework for Prompt-Induced Phase Transition in Large Language Modelscited by 2
  7. 2025Triggering Hallucinations in LLMs: A Quantitative Study of Prompt-Induced Hallucination in Large Language Modelscited by 2
  8. 2024Leveraging a Cognitive Model to Measure Subjective Similarity of Human and GPT-4 Written Contentcited by 1
  9. 2025NL2GenSym: Natural Language to Generative Symbolic Rules for SOAR Cognitive Architecture via Large Language Modelscited by 1
  10. 2025NL2CA: Auto-formalizing Cognitive Decision-Making from Natural Language Using an Unsupervised CriticNL2LTL Frameworkcited by 1
  11. 2024A New Type of Foundation Model Based on Recordings of People's Emotions and Physiologycited by 0
  12. 2024Recording First-person Experiences to Build a New Type of Foundation Modelcited by 0
3 more
  1. 2025The Way We Prompt: Conceptual Blending, Neural Dynamics, and Prompt-Induced Transitions in LLMscited by 0
  2. 2025Using Natural Language for Human-Robot Collaboration in the Real Worldcited by 0
  3. 2026Who Does This Name Remind You of ? Nationality Prediction via Large Language Model Associative Memorycited by 0

Similar, not cited

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  1. 2024Eliciting Problem Specifications via Large Language Models
  2. 2024Bootstrapping Cognitive Agents with a Large Language Model
  3. 2023Improving Knowledge Extraction from LLMs for Task Learning through Agent Analysis
  4. 2023Synergistic Integration of Large Language Models and Cognitive Architectures for Robust AI: An Exploratory Analysis
  5. 2026Cognitive Models and AI Algorithms Provide Templates for Designing Language Agents
  6. 2025From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Users
  7. 2023Brain in a Vat: On Missing Pieces Towards Artificial General Intelligence in Large Language Models
  8. 2026Can Small Agents Collaborate to Beat a Single Large Language Model?