mlsanityData to 7 Oct 2026

Non-Axiomatic Term Logic: A Computational Theory of Cognitive Symbolic Reasoning

arXiv 2210.06316 ↗First posted 12 Oct 2022cs.AI cs.LOcited by 1

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

This paper presents Non-Axiomatic Term Logic (NATL) as a theoretical computational framework of humanlike symbolic reasoning in artificial intelligence. NATL unites a discrete syntactic system inspired from Aristotle's term logic and a continuous semantic system based on the modern idea of distributed representations, or embeddings. This paper positions the proposed approach in the phylogeny and the literature of logic, and explains the framework. As it is yet no more than a theory and it requires much further elaboration to implement it, no quantitative evaluation is presented. Instead, qualitative analyses of arguments using NATL, some applications to possible cognitive science/robotics-related research, and remaining issues towards a machinery implementation are discussed.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 15 of its 63 references that are in the map. First posted on arXiv 12 Oct 2022.

Builds on

15 of 63 references.

References · 15

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,462
  4. 2021ByT5: Towards a token-free future with pre-trained byte-to-byte modelscited by 504
  5. 2018AllenNLP: A Deep Semantic Natural Language Processing Platformcited by 347
  6. 2015Towards AI-Complete Question Answering: A Set of Prerequisite Toy Taskscited by 309
  7. 2019Abductive Commonsense Reasoningcited by 300
  8. 2020COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphscited by 254
  9. 2019Probing Neural Network Comprehension of Natural Language Argumentscited by 212
  10. 2018Higher-order Coreference Resolution with Coarse-to-fine Inferencecited by 150
  11. 2021Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoningcited by 85
  12. 2021ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphscited by 78
3 more
  1. 2016Argumentation Mining in User-Generated Web Discoursecited by 69
  2. 2017The Argument Reasoning Comprehension Task: Identification and Reconstruction of Implicit Warrantscited by 55
  3. 2020Conversational Neuro-Symbolic Commonsense Reasoningcited by 28

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Citing papers per year: 2023: 1.

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  1. 2023Logical Reasoning over Natural Language as Knowledge Representation: A Survey
  2. 2022MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning
  3. 2025Current Practices for Building LLM-Powered Reasoning Tools Are Ad Hoc -- and We Can Do Better
  4. 2026Neuro-Symbolic Artificial Intelligence: A Task-Directed Survey in the Black-Box Models Era
  5. 2024Inference of Abstraction for a Unified Account of Symbolic Reasoning from Data
  6. 2023Enabling High-Level Machine Reasoning with Cognitive Neuro-Symbolic Systems
  7. 2022Is Neuro-Symbolic AI Meeting its Promise in Natural Language Processing? A Structured Review
  8. 2025Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems