| 2023 | A Hybrid System for Systematic Generalization in Simple Arithmetic Problems. Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti |
| 2023 | A Modular Neurosymbolic Approach for Visual Graph Question Answering. Thomas Eiter, Nelson Higuera Ruiz, Johannes Oetsch |
| 2023 | A Roadmap for Neuro-argumentative Learning. Maurizio Proietti, Francesca Toni |
| 2023 | Causality Prediction with Neural-Symbolic Systems: A Case Study in Smart Grids. Katrin Schreiberhuber, Marta Sabou, Fajar J. Ekaputra, Peter Knees, Peb Ruswono Aryan, Alfred Einfalt, Ralf Mosshammer |
| 2023 | Challenge Problems in Developing a Neuro-Symbolic OODA Loop. Alberto Speranzon, Christian H. Debrunner, David Rosenbluth, Mauricio Castillo-Effen, Anthony R. Nowicki, Kevin Alcedo, Andrzej Banaszuk |
| 2023 | Closing the Neural-Symbolic Cycle: Knowledge Extraction, User Intervention and Distillation from Convolutional Neural Networks. Kwun Ho Ngan, James Phelan, Esma Mansouri-Benssassi, Joe Townsend, Artur S. d'Avila Garcez |
| 2023 | Combining Machine Learning and Semantic Web: A Systematic Mapping Study. 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 |
| 2023 | Continual Reasoning: Non-monotonic Reasoning in Neurosymbolic AI using Continual Learning. Sofoklis Kyriakopoulos, Artur S. d'Avila Garcez |
| 2023 | Decoding Superpositions of Bound Symbols Represented by Distributed Representations. Michael Hersche, Zuzanna Opala, Geethan Karunaratne, Abu Sebastian, Abbas Rahimi |
| 2023 | Deep Symbolic Learning: Discovering Symbols and Rules from Perceptions. Alessandro Daniele, Tommaso Campari, Sagar Malhotra, Luciano Serafini |
| 2023 | Designing Logic Tensor Networks for Visual Sudoku Puzzle Classification. 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 Sebastian Russo, Marco Russo, Francesco Taioli, Lorenzo Vaiani, Chiara Vercellino |
| 2023 | Explainable Classification of Internet Memes. Abhinav Kumar Thakur, Filip Ilievski, Hông-Ân Sandlin, Zhivar Sourati, Luca Luceri, Riccardo Tommasini, Alain Mermoud |
| 2023 | Exploiting T-norms for Deep Learning in Autonomous Driving. Mihaela C. Stoian, Eleonora Giunchiglia, Thomas Lukasiewicz |
| 2023 | Exploring Mathematical Conjecturing with Large Language Models. Moa Johansson, Nicholas Smallbone |
| 2023 | FB15k-CVT: A Challenging Dataset for Knowledge Graph Embedding Models. Mouloud Iferroudjene, Victor Charpenay, Antoine Zimmermann |
| 2023 | From Axioms over Graphs to Vectors, and Back Again: Evaluating the Properties of Graph-based Ontology Embeddings. Fernando Zhapa-Camacho, Robert Hoehndorf |
| 2023 | Generalizable Neuro-Symbolic Systems for Commonsense Question Answering. Alessandro Oltramari, Jonathan Francis, Filip Ilievski, Kaixin Ma, Roshanak Mirzaee |
| 2023 | GlanceNets: Interpretable, Leak-proof Concept-based Models. Emanuele Marconato, Andrea Passerini, Stefano Teso |
| 2023 | How to Think About Benchmarking Neurosymbolic AI? Johanna Ott, Arthur Ledaguenel, Céline Hudelot, Mattis Hartwig |
| 2023 | Implementing Trustworthy AI in Real-world Medical Imaging using the SimpleMind Software Environment. Matthew S. Brown, M. Wasil Wahi-Anwar, Youngwon Choi, Morgan Daly, Liza Shrestha, Koon-Pong Wong, Jonathan G. Goldin, Dieter R. Enzmann |
| 2023 | Inductive Future Time Prediction on Temporal Knowledge Graphs with Interval Time. Roxana Pop, Egor V. Kostylev |
| 2023 | Interpretable Neural-Symbolic Concept Reasoning. Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Liò, Frédéric Precioso, Mateja Jamnik, Giuseppe Marra |
| 2023 | Is the Proof Length a Good Indicator of Hardness for Reason-able Embeddings? Jedrzej Potoniec |
| 2023 | Knowledge-Guided Colorization: Overview, Prospects and Challenges. Rory Ward, Muhammad Jaleed Khan, John G. Breslin, Edward Curry |
| 2023 | Large Language Models Need Symbolic AI. Kristian J. Hammond, David B. Leake |
| 2023 | Learning Logic Constraints From Demonstration. Mattijs Baert, Sam Leroux, Pieter Simoens |
| 2023 | Learning Where and When to Reason in Neuro-Symbolic Inference. Cristina Cornelio, Jan Stühmer, Shell Xu Hu, Timothy M. Hospedales |
| 2023 | Logic Explained Networks. Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci |
| 2023 | Neural Class Expression Synthesis. N'Dah Jean Kouagou, Stefan Heindorf, Caglar Demir, Axel-Cyrille Ngonga Ngomo |
| 2023 | Neural-Symbolic Predicate Invention: Learning Relational Concepts from Visual Scenes. Jingyuan Sha, Hikaru Shindo, Kristian Kersting, Devendra Singh Dhami |
| 2023 | Neuro-Symbolic Reasoning Shortcuts: Mitigation Strategies and their Limitations. Emanuele Marconato, Stefano Teso, Andrea Passerini |
| 2023 | On the Benefits of OWL-based Knowledge Graphs for Neural-Symbolic Systems. David Herron, Ernesto Jiménez-Ruiz, Tillman Weyde |
| 2023 | PhysWM: Physical World Models for Robot Learning. Marc Otto, Octavio Arriaga, Chandandeep Singh, Jichen Guo, Frank Kirchner |
| 2023 | Preliminary Results on a State-Driven Method for Rule Construction in Neural-Symbolic Reinforcement Learning. Davide Beretta, Stefania Monica, Federico Bergenti |
| 2023 | Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning, La Certosa di Pontignano, Siena, Italy, July 3-5, 2023. Artur S. d'Avila Garcez, Tarek R. Besold, Marco Gori, Ernesto Jiménez-Ruiz |
| 2023 | RL-Net: Interpretable Rule Learning with Neural Networks. Lucile Dierckx, Rosana Veroneze, Siegfried Nijssen |
| 2023 | Safe Reinforcement Learning via Probabilistic Logic Shields. Wen-Chi Yang, Giuseppe Marra, Gavin Rens, Luc De Raedt |
| 2023 | Semantic Interpretability of Convolutional Neural Networks by Taxonomy Extraction. Vitor A. C. Horta, Robin Sobczyk, Maarten C. Stol, Alessandra Mileo |
| 2023 | Semantic Probabilistic Layers for Neuro-Symbolic Learning. Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari |
| 2023 | Solving Raven's Progressive Matrices via a Neuro-vector-symbolic Architecture. Michael Hersche, Mustafa Zeqiri, Luca Benini, Abu Sebastian, Abbas Rahimi |
| 2023 | The Challenge of Learning Symbolic Representations. Luca Salvatore Lorello, Marco Lippi |
| 2023 | The Roles of Symbols in Neural-based AI: They are Not What You Think! Daniel L. Silver, Tom M. Mitchell |
| 2023 | Towards Explainable Decision Making with Neural Program Synthesis and Library Learning. Manuel Eberhardinger, Johannes Maucher, Setareh Maghsudi |
| 2023 | Towards Invertible Semantic-Preserving Embeddings of Logical Formulae. Gaia Saveri, Luca Bortolussi |
| 2023 | VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming. Eleonora Misino, Giuseppe Marra, Emanuele Sansone |
| 2023 | VSA-based Positional Encoding Can Replace Recurrent Networks in Emergent Symbol Binding. Francesco S. Carzaniga, Michael Hersche, Kaspar Schindler, Abbas Rahimi |
| 2023 | Verifying Strategic Abilities of Neural-Symbolic Multi-agent Systems. Michael Akintunde, Elena Botoeva, Panagiotis Kouvaros, Alessio Lomuscio |
| 2023 | Visual Reward Machines. Elena Umili, Francesco Argenziano, Aymeric Barbin, Roberto Capobianco |
| 2023 | What's Wrong with Gradient-based Complex Query Answering? Ouns El Harzli, Samy Badreddine, Tarek R. Besold |