NeSy 2023
Neural-Symbolic Learning and Reasoning 2023

Table of Contents

• Preface
  Summary: There were 67 papers submitted for peer-review to this workshop. Out of these, 48 papers were accepted for this volume.

Research papers track

• A Roadmap for Neuro-argumentative Learning (short paper) 1-8
  Maurizio Proietti , Francesca Toni
• What's Wrong with Gradient-based Complex Query Answering? 9-18
  Ouns El Harzli , Samy Badreddine , Tarek R. Besold
• Closing the Neural-Symbolic Cycle: Knowledge Extraction, User Intervention and Distillation from Convolutional Neural Networks 19-43
  Kwun Ho Ngan , James Phelan , Esma Mansouri-Benssassi , Joe Townsend , Artur S. d'Avila Garcez
• The Challenge of Learning Symbolic Representations 44-61
  Luca Salvatore Lorello , Marco Lippi
• Exploring Mathematical Conjecturing with Large Language Models 62-77
  Moa Johansson , Nicholas Smallbone
• Learning Logic Constraints From Demonstration (short paper) 78-84
  Mattijs Baert , Sam Leroux , Pieter Simoens
• From Axioms over Graphs to Vectors, and Back Again: Evaluating the Properties of Graph-based Ontology Embeddings 85-102
  Fernando Zhapa-Camacho , Robert Hoehndorf
• Neural-Symbolic Predicate Invention: Learning Relational Concepts from Visual Scenes 103-117
  Jingyuan Sha , Hikaru Shindo , Kristian Kersting , Devendra Singh Dhami
• Semantic Interpretability of Convolutional Neural Networks by Taxonomy Extraction 118-127
  Vitor A. C. Horta , Robin Sobczyk , Maarten C. Stol , Alessandra Mileo
• Preliminary Results on a State-Driven Method for Rule Construction in Neural-Symbolic Reinforcement Learning 128-138
  Davide Beretta , Stefania Monica , Federico Bergenti
• A Modular Neurosymbolic Approach for Visual Graph Question Answering 139-149
  Thomas Eiter , Nelson Higuera Ruiz , Johannes Oetsch
• Is the Proof Length a Good Indicator of Hardness for Reason-able Embeddings? 150-161
  Jędrzej Potoniec
• Neuro-Symbolic Reasoning Shortcuts: Mitigation Strategies and their Limitations (short paper) 162-166
  Emanuele Marconato , Stefano Teso , Andrea Passerini
• Knowledge-Guided Colorization: Overview, Prospects and Challenges (short paper) 167-173
  Rory Ward , M. Jaleed Khan , John G. Breslin , Edward Curry
• Towards Invertible Semantic-Preserving Embeddings of Logical Formulae 174-194
  Gaia Saveri , Luca Bortolussi
• Implementing Trustworthy AI in Real-world Medical Imaging using the SimpleMind Software Environment (short paper) 195-203
  Matthew S. Brown , M. Wasil Wahi-Anwar , Youngwon Choi , Morgan Daly , Liza Shrestha , Koon-Pong Wong , Jonathan G. Goldin , Dieter R. Enzmann
• Large Language Models Need Symbolic AI (short paper) 204-209
  Kristian Hammond , David Leake
• Continual Reasoning: Non-monotonic Reasoning in Neurosymbolic AI using Continual Learning 210-222
  Sofoklis Kyriakopoulos , Artur S. d'Avila Garcez
• Designing Logic Tensor Networks for Visual Sudoku Puzzle Classification 223-232
  Lia Morra , Alberto Azzari , Letizia Bergamasco , Marco Braga , Luigi Capogrosso , Federico Delrio , Giuseppe Di Giacomo , Simone Eiraudo , Giorgia Ghione , Rocco Giudice , Alkis Koudounas , Luca Piano , Daniele Rege Cambrin , Matteo Risso , Marco Rondina , Alessandro Sebastien Russo , Marco Russo , Francesco Taioli , Lorenzo Vaiani , Chiara Vercellino
• Inductive Future Time Prediction on Temporal Knowledge Graphs with Interval Time (short paper) 233-240
  Roxana Pop , Egor V. Kostylev
• Challenge Problems in Developing a Neuro-Symbolic OODA Loop (short paper) 241-247
  Alberto Speranzon , Christian H. Debrunner , David Rosenbluth , Mauricio Castillo-Effen , Anthony R. Nowicki , Kevin Alcedo , Andrzej Banaszuk
• How to Think About Benchmarking Neurosymbolic AI? (short paper) 248-254
  Johanna Ott , Arthur Ledaguenel , Céline Hudelot , Mattis Hartwig
• Visual Reward Machines 255-267
  Elena Umili , Francesco Argenziano , Aymeric Barbin , Roberto Capobianco
• PhysWM: Physical World Models for Robot Learning 268-278
  Marc Otto , Octavio Arriaga , Chandandeep Singh , Jichen Guo , Frank Kirchner
• Decoding Superpositions of Bound Symbols Represented by Distributed Representations 279-288
  Michael Hersche , Zuzanna Opala , Geethan Karunaratne , Abu Sebastian , Abbas Rahimi
• A Hybrid System for Systematic Generalization in Simple Arithmetic Problems 289-301
  Flavio Petruzzellis , Alberto Testolin , Alessandro Sperduti
• VSA-based Positional Encoding Can Replace Recurrent Networks in Emergent Symbol Binding 302-326
  Francesco S. Carzaniga , Michael Hersche , Kaspar Schindler , Abbas Rahimi
• On the Benefits of OWL-based Knowledge Graphs for Neural-Symbolic Systems (short paper) 327-335
  David Herron , Ernesto Jiménez-Ruiz , Tillman Weyde
• Causality Prediction with Neural-Symbolic Systems: A Case Study in Smart Grids 336-347
  Katrin Schreiberhuber , Marta Sabou , Fajar J. Ekaputra , Peter Knees , Peb Ruswono Aryan , Alfred Einfalt , Ralf Mosshammer
• Towards Explainable Decision Making with Neural Program Synthesis and Library Learning 348-368
  Manuel Eberhardinger , Johannes Maucher , Setareh Maghsudi
• Exploiting T-norms for Deep Learning in Autonomous Driving 369-380
  Mihaela C. Stoian , Eleonora Giunchiglia , Thomas Lukasiewicz
• FB15k-CVT: A Challenging Dataset for Knowledge Graph Embedding Models 381-394
  Mouloud Iferroudjene , Victor Charpenay , Antoine Zimmermann
• Explainable Classification of Internet Memes 395-409
  Abhinav Kumar Thakur , Filip Ilievski , Hông-Ân Sandlin , Zhivar Sourati , Luca Luceri , Riccardo Tommasini , Alain Mermoud

Recently published papers track (extended abstracts)

• GlanceNets: Interpretable, Leak-proof Concept-based Models 410-410
  Emanuele Marconato , Andrea Passerini , Stefano Teso
• Learning Where and When to Reason in Neuro-Symbolic Inference 411-412
  Cristina Cornelio , Jan Stuemer , Shell Xu Hu , Timothy Hospedales
• Semantic Probabilistic Layers for Neuro-Symbolic Learning 413-413
  Kareem Ahmed , Stefano Teso , Kai-Wei Chang , Guy Van den Broeck , Antonio Vergari
• RL-Net: Interpretable Rule Learning with Neural Networks 414-415
  Lucile Dierckx , Rosana Veroneze , Siegfried Nijssen
• Generalizable Neuro-Symbolic Systems for Commonsense Question Answering 416-417
  Alessandro Oltramari , Jonathan Francis , Filip Ilievski , Kaixin Ma , Roshanak Mirzaee
• Deep Symbolic Learning: Discovering Symbols and Rules from Perceptions 418-419
  Alessandro Daniele , Tommaso Campari , Sagar Malhotra , Luciano Serafini
• The Roles of Symbols in Neural-based AI: They are Not What You Think! 420-421
  Daniel L. Silver , Tom M. Mitchell
• Interpretable Neural-Symbolic Concept Reasoning 422-423
  Pietro Barbiero , Gabriele Ciravegna , Francesco Giannini , Mateo Espinosa Zarlenga , Lucie Charlotte Magister , Alberto Tonda , Pietro Liò , Frederic Precioso , Mateja Jamnik , Giuseppe Marra
• Combining Machine Learning and Semantic Web: A Systematic Mapping Study 424-424
  Anna Breit , Laura Waltersdorfer , Fajar J. Ekaputra , Marta Sabou , Andreas Ekelhart , Andreea Iana , Heiko Paulheim , Jan Portisch , Artem Revenko , Frank van Harmelen , Annette ten Teije
• Solving Raven's Progressive Matrices via a Neuro-vector-symbolic Architecture 425-426
  Michael Hersche , Mustafa Zeqiri , Luca Benini , Abu Sebastian , Abbas Rahimi
• Verifying Strategic Abilities of Neural-Symbolic Multi-agent Systems 427-427
  Michael Akintunde , Elena Botoeva , Panagiotis Kouvaros , Alessio Lomuscio
• Safe Reinforcement Learning via Probabilistic Logic Shields 428-429
  Wen-Chi Yang , Giuseppe Marra , Gavin Rens , Luc De Raedt
• Neural Class Expression Synthesis 430-431
  N'Dah Jean Kouagou , Stefan Heindorf , Caglar Demir , Axel-Cyrille Ngonga Ngomo
• Logic Explained Networks 432-433
  Gabriele Ciravegna , Pietro Barbiero , Francesco Giannini , Marco Gori , Pietro Liò , Marco Maggini , Stefano Melacci
• VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming 434-435
  Eleonora Misino , Giuseppe Marra , Emanuele Sansone