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Neural-Symbolic Learning and Reasoning

18th International Conference, NeSy 2024, Barcelona, Spain, September 9–12, 2024, Proceedings, Part II

  • Conference proceedings
  • © 2024

Overview

Editors:
  1. Tarek R. Besold

    1. Sony AI, Barcelona, Spain

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  2. Artur d’Avila Garcez

    1. City, University of London, London, UK

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  3. Ernesto Jimenez-Ruiz

    1. City, University of London, London, UK

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  4. Roberto Confalonieri

    1. University of Padova, Padova, Italy

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  5. Pranava Madhyastha

    1. City, University of London, London, UK

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  6. Benedikt Wagner

    1. City, University of London, London, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14980)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: NeSy 2024.

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About this book

This book constitutes the refereed proceedings of the 18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024, held in Barcelona, Spain during September 9-12th, 2024.

The 30 full papers and 18 short papers were carefully reviewed and selected from 89 submissions, which presented the latest and ongoing research work on neurosymbolic AI. Neurosymbolic AI aims to build rich computational models and systems by combining neural and symbolic learning and reasoning paradigms. This combination hopes to form synergies among their strengths while overcoming their
complementary weaknesses.

Keywords

Table of contents (26 papers)

  1. Front Matter

    Pages i-xxiii
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  2. NeSy 2024 Papers

    1. Front Matter

      Pages 1-1
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    2. IID Relaxation by Logical Expressivity: A Research Agenda for Fitting Logics to Neurosymbolic Requirements

      • Maarten C. Stol, Alessandra Mileo
      Pages 3-13

    3. Enhancing Neuro-Symbolic Integration with Focal Loss: A Study on Logic Tensor Networks

      • Luca Piano, Francesco Manigrasso, Alessandro Russo, Lia Morra
      Pages 14-23

    4. WineGraph: A Graph Representation for Food-Wine Pairing

      • Zuzanna Gawrysiak, Agata Żywot, Agnieszka Ławrynowicz
      Pages 24-31

    5. Logic Supervised Learning for Time Series - Continual Learning for Appliance Detection

      • Benjamin Duppe
      Pages 32-40

    6. Towards Understanding the Impact of Graph Structure on Knowledge Graph Embeddings

      • Brandon Dave, Antrea Christou, Cogan Shimizu
      Pages 41-50

    7. Commonsense Ontology Micropatterns

      • Andrew Eells, Brandon Dave, Pascal Hitzler, Cogan Shimizu
      Pages 51-59

    8. Metacognitive AI: Framework and the Case for a Neurosymbolic Approach

      • Hua Wei, Paulo Shakarian, Christian Lebiere, Bruce Draper, Nikhil Krishnaswamy, Sergei Nirenburg
      Pages 60-67

    9. Enhancing Logical Tensor Networks: Integrating Uninorm-Based Fuzzy Operators for Complex Reasoning

      • Paulo Vitor de Campos Souza, Gianluca Apriceno, Mauro Dragoni
      Pages 68-79

    10. Parameter Learning Using Approximate Model Counting

      • Lucile Dierckx, Alexandre Dubray, Siegfried Nijssen
      Pages 80-88

    11. Large-Scale Knowledge Integration for Enhanced Molecular Property Prediction

      • Yasir Ghunaim, Robert Hoehndorf
      Pages 89-97

    12. Towards Understanding Graph Neural Networks: Functional-Semantic Activation Mapping

      • Kislay Raj, Alessandra Mileo
      Pages 98-106

  3. NeSy 2024 XAI Special Track

    1. Front Matter

      Pages 107-107
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    2. On the Value of Labeled Data and Symbolic Methods for Hidden Neuron Activation Analysis

      • Abhilekha Dalal, Rushrukh Rayan, Adrita Barua, Eugene Y. Vasserman, Md Kamruzzaman Sarker, Pascal Hitzler
      Pages 109-131

    3. Concept Induction Using LLMs: A User Experiment for Assessment

      • Adrita Barua, Cara Widmer, Pascal Hitzler
      Pages 132-148

    4. Error-Margin Analysis for Hidden Neuron Activation Labels

      • Abhilekha Dalal, Rushrukh Rayan, Pascal Hitzler
      Pages 149-164

    5. LENs for Analyzing the Quality of Life of People with Intellectual Disability

      • Diego Fraile-Parra, Vicent Costa, Pilar Dellunde
      Pages 165-174

    6. ECATS: Explainable-by-Design Concept-Based Anomaly Detection for Time Series

      • Irene Ferfoglia, Gaia Saveri, Laura Nenzi, Luca Bortolussi
      Pages 175-191

    7. Bringing Back Semantics to Knowledge Graph Embeddings: An Interpretability Approach

      • Antoine Domingues, Nitisha Jain, Albert Meroño Peñuela, Elena Simperl
      Pages 192-203
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Other volumes

  1. Neural-Symbolic Learning and Reasoning

  2. Neural-Symbolic Learning and Reasoning

Editors and Affiliations

  • Sony AI, Barcelona, Spain

    Tarek R. Besold

  • City, University of London, London, UK

    Artur d’Avila Garcez, Ernesto Jimenez-Ruiz, Pranava Madhyastha, Benedikt Wagner

  • University of Padova, Padova, Italy

    Roberto Confalonieri

Bibliographic Information

  • Book Title: Neural-Symbolic Learning and Reasoning

  • Book Subtitle: 18th International Conference, NeSy 2024, Barcelona, Spain, September 9–12, 2024, Proceedings, Part II

  • Editors: Tarek R. Besold, Artur d’Avila Garcez, Ernesto Jimenez-Ruiz, Roberto Confalonieri, Pranava Madhyastha, Benedikt Wagner

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-71170-1

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024

  • Softcover ISBN: 978-3-031-71169-5Published: 10 September 2024

  • eBook ISBN: 978-3-031-71170-1Published: 09 September 2024

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XXIII, 341

  • Number of Illustrations: 19 b/w illustrations, 74 illustrations in colour

  • Topics: Software Engineering/Programming and Operating Systems, Artificial Intelligence

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