mlsanityData to 14 Oct 2026

ChatDB: Augmenting LLMs with Databases as Their Symbolic Memory

arXiv 2306.03901 ↗First posted 6 Jun 2023cs.AI cs.CL cs.DBcited by 140

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Cited by 61 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Large language models (LLMs) with memory are computationally universal. However, mainstream LLMs are not taking full advantage of memory, and the designs are heavily influenced by biological brains. Due to their approximate nature and proneness to the accumulation of errors, conventional neural memory mechanisms cannot support LLMs to simulate complex reasoning. In this paper, we seek inspiration from modern computer architectures to augment LLMs with symbolic memory for complex multi-hop reasoning. Such a symbolic memory framework is instantiated as an LLM and a set of SQL databases, where the LLM generates SQL instructions to manipulate the SQL databases. We validate the effectiveness of the proposed memory framework on a synthetic dataset requiring complex reasoning. The project website is available at https://chatdatabase.github.io/ .

Key facts. Cited by 140 papers in the map (data through 14 Oct 2026). Builds on 35 of its 38 references that are in the map. First posted on arXiv 6 Jun 2023.

Builds on

35 of 38 references.

References · 35

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2023GPT-4 Technical Reportcited by 18,396
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  7. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
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  12. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,141
23 more
  1. 2023HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Facecited by 1,190
  2. 2023PaLM 2 Technical Reportcited by 1,162
  3. 2022Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Taskscited by 1,076
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  9. 2023ViperGPT: Visual Inference via Python Execution for Reasoningcited by 603
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  18. 2019NumNet: Machine Reading Comprehension with Numerical Reasoningcited by 59
  19. 2019Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehensioncited by 51
  20. 2023Memory Augmented Large Language Models are Computationally Universalcited by 47
  21. 2022An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Taskscited by 36
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 24; 2024: 54; 2025: 30; 2026: 32.

140 papers.

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  6. 2023MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Usecited by 217
  7. 2025A Survey of Context Engineering for Large Language Modelscited by 126
  8. 2025G-Memory: Tracing Hierarchical Memory for Multi-Agent Systemscited by 122
  9. 2024Empowering Biomedical Discovery with AI Agentscited by 118
  10. 2024HiAgent: Hierarchical Working Memory Management for Solving Long-Horizon Agent Tasks with Large Language Modelcited by 106
  11. 2023MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversationcited by 97
  12. 2024KG-Agent: An Efficient Autonomous Agent Framework for Complex Reasoning over Knowledge Graphcited by 93
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  2. 2025Lifelong Learning of Large Language Model based Agents: A Roadmapcited by 83
  3. 2024From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agentscited by 82
  4. 2024TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarioscited by 77
  5. 2023Data-Copilot: Bridging Billions of Data and Humans with Autonomous Workflowcited by 76
  6. 2024Tell Me More! Towards Implicit User Intention Understanding of Language Model Driven Agentscited by 74
  7. 2023Igniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agentscited by 72
  8. 2024TableGPT2: A Large Multimodal Model with Tabular Data Integrationcited by 72
  9. 2024A Survey on Employing Large Language Models for Text-to-SQL Taskscited by 67
  10. 2026Memory for Autonomous LLM Agents:Mechanisms, Evaluation, and Emerging Frontierscited by 65
  11. 2023Dynamic Planning with a LLMcited by 61
  12. 2023TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPTcited by 59
  13. 2024DoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models (Exemplified as A Video Agent)cited by 58
  14. 2024KG-RAG: Bridging the Gap Between Knowledge and Creativitycited by 56
  15. 2023From Prompt Injections to SQL Injection Attacks: How Protected is Your LLM-Integrated Web Application?cited by 55
  16. 2025M+: Extending MemoryLLM with Scalable Long-Term Memorycited by 54
  17. 2023KnowledGPT: Enhancing Large Language Models with Retrieval and Storage Access on Knowledge Basescited by 52
  18. 2024Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMscited by 48
  19. 2024Enhance Reasoning for Large Language Models in the Game Werewolfcited by 46
  20. 2023Large Language Models are Zero Shot Hypothesis Proposerscited by 45
  21. 2026A Survey of Agent Memory in the Second Half: Towards Self-Evolving and Long-Horizon Agentscited by 44
  22. 2023Large Language Models Are Semi-Parametric Reinforcement Learning Agentscited by 42
  23. 2024TravelAgent: An AI Assistant for Personalized Travel Planningcited by 39
  24. 2024KARMA: Augmenting Embodied AI Agents with Long-and-short Term Memory Systemscited by 39
  25. 2023LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent Ecosystemcited by 38
  26. 2025Rethinking Memory in LLM based Agents: Representations, Operations, and Emerging Topicscited by 36
  27. 2024MemLLM: Finetuning LLMs to Use An Explicit Read-Write Memorycited by 35
  28. 2024PerLTQA: A Personal Long-Term Memory Dataset for Memory Classification, Retrieval, and Synthesis in Question Answeringcited by 34
  29. 2024Large Language Models as Biomedical Hypothesis Generators: A Comprehensive Evaluationcited by 34
  30. 2023ALYMPICS: LLM Agents Meet Game Theory -- Exploring Strategic Decision-Making with AI Agentscited by 33
  31. 2024RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewardscited by 33
  32. 2023Never Lost in the Middle: Mastering Long-Context Question Answering with Position-Agnostic Decompositional Trainingcited by 32
  33. 2023TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoningcited by 32
  34. 2024A Survey of Useful LLM Evaluationcited by 29
  35. 2024G"odel Agent: A Self-Referential Agent Framework for Recursive Self-Improvementcited by 29
  36. 2024Emotional RAG: Enhancing Role-Playing Agents through Emotional Retrievalcited by 26
  37. 2023LARP: Language-Agent Role Play for Open-World Gamescited by 24
  38. 2024MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistantscited by 24

50 most cited of 140 All 140 (JSON)

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  4. 2023Large Language Models Are Not Strong Abstract Reasoners
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  6. 2026ORACLE: Optimizing Reasoning Abilities of Large Language Models via Constraint-Led Synthetic Data Elicitation
  7. 2025Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs
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