Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: MRKL Systems: A modular, neuro-symbolic architecture that combines large
  language models, external knowledge sources and discrete reasoning   Huge language models (LMs) have ushered in a new era for AI, serving as a
gateway to natural-language-based knowledge tasks. Although an essential
element of modern AI, LMs are also inherently limited in a number of ways. We
discuss these limitations and how they can be avoided by adopting a systems
approach. Conceptualizing the challenge as one that involves knowledge and
reasoning in addition to linguistic processing, we define a flexible
architecture with multiple neural models, complemented by discrete knowledge
and reasoning modules. We describe this neuro-symbolic architecture, dubbed the
Modular Reasoning, Knowledge and Language (MRKL, pronounced "miracle") system,
some of the technical challenges in implementing it, and Jurassic-X, AI21 Labs'
MRKL system implementation.

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The categories of this paper are: quant-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: nucl-th
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The categories of this paper are: cond-mat
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The categories of this paper are: physics
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The categories of this paper are: atom-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: nucl-ex
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The categories of this paper are: econ
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The categories of this paper are: solv-int
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The categories of this paper are: acc-phys
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The categories of this paper are: gr-qc
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The categories of this paper are: chao-dyn
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The categories of this paper are: plasm-ph
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The categories of this paper are: math
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The categories of this paper are: math-ph