mlsanityData to 14 Oct 2026

Neuro-symbolic Commonsense Social Reasoning

arXiv 2303.08264 ↗First posted 14 Mar 2023cs.AIcited by 5

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Abstract (arXiv)

Social norms underlie all human social interactions, yet formalizing and reasoning with them remains a major challenge for AI systems. We present a novel system for taking social rules of thumb (ROTs) in natural language from the Social Chemistry 101 dataset and converting them to first-order logic where reasoning is performed using a neuro-symbolic theorem prover. We accomplish this in several steps. First, ROTs are converted into Abstract Meaning Representation (AMR), which is a graphical representation of the concepts in a sentence, and align the AMR with RoBERTa embeddings. We then generate alternate simplified versions of the AMR via a novel algorithm, recombining and merging embeddings for added robustness against different wordings of text, and incorrect AMR parses. The AMR is then converted into first-order logic, and is queried with a neuro-symbolic theorem prover. The goal of this paper is to develop and evaluate a neuro-symbolic method which performs explicit reasoning about social situations in a logical form.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 17 of its 31 references that are in the map. First posted on arXiv 14 Mar 2023.

Builds on

17 of 31 references.

References · 17

  1. 2017Attention Is All You Needcited by 60,361
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  8. 2016A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Storiescited by 417
  9. 2021Persistent Anti-Muslim Bias in Large Language Modelscited by 377
  10. 2020Social Chemistry 101: Learning to Reason about Social and Moral Normscited by 255
  11. 2018Gender Bias in Neural Natural Language Processingcited by 211
  12. 2017End-to-End Differentiable Provingcited by 161
5 more
  1. 2020Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequencescited by 135
  2. 2020Leveraging Abstract Meaning Representation for Knowledge Base Question Answeringcited by 53
  3. 2021Maximum Bayes Smatch Ensemble Distillation for AMR Parsingcited by 29
  4. 2022Inducing and Using Alignments for Transition-based AMR Parsingcited by 12
  5. 2020Braid: Weaving Symbolic and Neural Knowledge into Coherent Logical Explanationscited by 11

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 2.

5 papers.