A Case-Based Persistent Memory for a Large Language Model
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Abstract (arXiv)
Case-based reasoning (CBR) as a methodology for problem-solving can use any appropriate computational technique. This position paper argues that CBR researchers have somewhat overlooked recent developments in deep learning and large language models (LLMs). The underlying technical developments that have enabled the recent breakthroughs in AI have strong synergies with CBR and could be used to provide a persistent memory for LLMs to make progress towards Artificial General Intelligence.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 29 references that are in the map. First posted on arXiv 13 Oct 2023.
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6 of 29 references.
References · 6
- 2017Attention Is All You Needcited by 59,932
- 2018This Looks Like That: Deep Learning for Interpretable Image Recognitioncited by 731
- 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 695
- 2023A Survey of Hallucination in Large Foundation Modelscited by 365
- 2023Case-Based Reasoning with Language Models for Classification of Logical Fallaciescited by 8
- 2021Twin Systems for DeepCBR: A Menagerie of Deep Learning and Case-Based Reasoning Pairings for Explanation and Data Augmentationcited by 3
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