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Proceedings of Machine Learning Research

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Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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Volume 284: Conference on Neurosymbolic Learning and Reasoning, 8-10 September 2025, UC Santa Cruz, Santa Cruz, CA, USA

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Editors: Leilani H. Gilpin, Eleonora Giunchiglia, Pascal Hitzler, Emile van Krieken

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Adapting Graph-Based Analysis for Knowledge Extraction from Transformer Models

; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:1-14

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Do Graph Neural Network States Contain Graph Properties?

Tom Pelletreau-Duris, Ruud van Bakel, Michael Cochez; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:15-51

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A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification

Vasileios Manginas, Nikolaos Manginas, Edward Stevinson, Sherwin Varghese, Nikos Katzouris, Georgios Paliouras, Alessio Lomuscio; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:52-69

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SymDQN: Symbolic Knowledge and Reasoning in Neural Network-based Reinforcement Learning

Ivo Amador, Nina Gierasimczuk; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:70-85

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Bridging Neural and Symbolic Computation: A Learnability Study of RNNs on Counter and Dyck Languages

Neisarg Dave, Daniel Kifer, C. Lee Giles, Ankur Mali; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:86-115

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High Quality Embeddings for Horn Logic Reasoning

Yifan Zhang, Yasir White, Dean Clark, Joseph Sanchez, Jevon Lipsey, Ashely Hirst, Jeff Heflin; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:116-129

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Grounding Terms from an Ontology for use in Autoformalization: Tokenization is All You Need

Richard Thompson, Adam Pease, Mathias Kölsch, Angelos Toutsios; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:130-136

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Rethinking Reasoning in LLMs: Neuro-Symbolic Local RetoMaton Beyond CoT and ICL

Rushitha Santhoshi Mamidala, Anshuman Chhabra, Ankur Mali; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:137-159

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Description Logic Concept Learning using Large Language Models

Adrita Barua, Pascal Hitzler; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:160-178

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Toward a Clearer Characterization of Neuro-Symbolic Frameworks: A Brief Comparative Analysis

Sania Sinha, Tanawan Premsri, Parisa Kordjamshidi; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:179-217

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Practical Lessons on Vector-Symbolic Architectures in Deep Learning-Inspired Environments

Francesco S. Carzaniga, Michael Hersche, Kaspar Schindler, Abbas Rahimi; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:218-236

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Concept Probing: Where to Find Human-Defined Concepts

Manuel de Sousa Ribeiro, Afonso Leote, Joao Leite; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:237-251

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T-ILR: a Neurosymbolic Integration for LTLf

Riccardo Andreoni, Andrei Buliga, Alessandro Daniele, Chiara Ghidini, Marco Montali, Massimiliano Ronzani; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:252-265

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Hierarchical Neuro-Symbolic Decision Transformer

Ali Baheri, Cecilia Alm; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:266-284

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Neurosymbolic Reasoning Shortcuts under the Independence Assumption

Emile van Krieken, Pasquale Minervini, Edoardo Ponti, Antonio Vergari; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:285-302

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Understanding the Expressive Capabilities of Knowledge Base Embeddings under Box Semantics

Mena Leemhuis, Oliver Kutz; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:303-321

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Neural-Symbolic Architectural Axioms of Integration: A Manifesto

Connor Pryor, Lise Getoor; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:322-342

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CRAFT: A Neuro-Symbolic Framework for Visual Functional Affordance Grounding

Zhou Chen, Joe Lin, Sathyanarayanan N. Aakur; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:343-352

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Generating Safety-Critical Automotive C-programs using LLMs with Formal Verification

Merlijn Sevenhuijsen, Minal Suresh Patil, Mattias Nyberg, Gustav Ung; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:353-378

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Talking to GDELT Through Knowledge Graphs

Audun D Myers, Max Vargas, Sinan Guven Aksoy, Cliff Joslyn, Benjamin Wilson, Lee Burke, Tom Grimes; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:379-391

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Sound and Complete Neurosymbolic Reasoning with LLM-Grounded Interpretations

Bradley P. Allen, Prateek Chhikara, Thomas Macaulay Ferguson, Filip Ilievski, Paul Groth; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:392-419

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Towards a Neurosymbolic Reasoning System Grounded in Schematic Representations

François Olivier, Zied Bouraoui; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:420-438

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Exploring Verification Frameworks for Social Choice Alignment

Jessica Ciupa, Vaishak Belle, Ekaterina Komendantskaya; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:439-446

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A Comparative Study of Neurosymbolic AI Approaches to Interpretable Logical Reasoning

Michael K. Chen; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:447-462

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Disentangling Neural Disjunctive Normal Form Models

Kexin Gu Baugh, Vincent Perreault, Matthew Baugh, Luke Dickens, Katsumi Inoue, Alessandra Russo; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:463-493

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mULLER: A Modular Monad-Based Semantics of the Neurosymbolic ULLER Framework

Daniel Romero Schellhorn, Till Mossakowski; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:494-518

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The ART of Link Prediction with KGEs

Yannick Brunink, Michael Cochez, Jacopo Urbani; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:519-539

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SymRAG: Efficient Neuro-Symbolic Retrieval Through Adaptive Query Routing

Safayat Bin Hakim, Muhammad Adil, Alvaro Velasquez, Houbing Herbert Song; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:540-564

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Neurosymbolic Association Rule Mining from Tabular Data

Erkan Karabulut, Paul Groth, Victoria Degeler; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:565-588

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Neurosymbolic Tag-Based Annotation for Interpretable Avatar Creation

Minghao Liu, Zeyu Cheng, Shen Sang, Jing Liu, James Davis; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:589-624

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Bridging Bots: from Perception to Action via Multimodal-LMs and Knowledge Graphs

Margherita Martorana, Francesca Urgese, Mark Adamik, Ilaria Tiddi; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:625-646

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JARVIS: A Neuro-Symbolic Commonsense Reasoning Framework for Conversational Embodied Agents

Kaizhi Zheng, Kaiwen Zhou, Jing Gu, Yue Fan, Jialu Wang, Zonglin Di, Xuehai He, Xin Eric Wang; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:647-673

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A Comparative Analysis of Neurosymbolic Methods for Link Prediction

Guillaume Delplanque, Luisa Werner, Nabil Layaïda, Pierre Geneves; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:674-696

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ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentation

Yuqicheng Zhu, Nico Potyka, Daniel Hernández, Yuan He, Zifeng Ding, Bo Xiong, Dongzhuoran Zhou, Evgeny Kharlamov, Steffen Staab; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:697-718

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Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic Models

Marcio Nicolau, Anderson R. Tavares, Zhiwei Zhang, Pedro H. C. Avelar, João Marcos Flach, Luis DC Lamb, Moshe Vardi; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:719-735

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Distilling KGE black boxes into interpretable NeSy models

Rodrigo Castellano Ontiveros, Francesco Giannini, Michelangelo Diligenti; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:736-749

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Can Large Reasoning Models do Analogical Reasoning under Perceptual Uncertainty?

Giacomo Camposampiero, Michael Hersche, Roger Wattenhofer, Abu Sebastian, Abbas Rahimi; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:750-776

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Act-to-Ground: A Framework for Symbol Grounding in Planning Domains

Panagiotis Lymperopoulos, Liping Liu; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:777-795

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Neurosymbolic models based on hybrids of convolutional neural networks and decision trees

Rasul Kairgeldin, Miguel Á. Carreira-Perpiñán; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:796-813

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Neural Theorem Proving: Generating and Structuring Proofs for Formal Verification

Balaji Rao, William Eiers, Carlo Lipizzi; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:814-829

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Towards Explainable Depression Detection: A Neurosymbolic Approach to Uncover Social Media Signals with Generative AI

Mohammad Saeid Mahdavinejad, Peyman Adibi, Amirhassan Monajemi, Pascal Hitzler; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:830-853

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Bayesian Inverse Physics for Neuro-Symbolic Robot Learning

Octavio Arriaga, Rebecca Carrie Adam, Melvin Laux, Lisa Gutzeit, Marco Ragni, Jan Peters, Frank Kirchner; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:854-872

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Gestalt Vision: A Dataset for Evaluating Gestalt Principles in Visual Perception

Jingyuan Sha, Hikaru Shindo, Kristian Kersting, Devendra Singh Dhami; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:873-890

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Ontology-based box embeddings and knowledge graphs for predicting phenotypic traits in Saccharomyces cerevisiae

Filip Kronström, Daniel Brunnsåker, Ievgeniia A. Tiukova, Ross D. King; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:891-912

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Neuro-Symbolic Inverse Constrained Reinforcement Learning

Oliver Deane, Oliver Ray; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:913-925

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MC3G: Model Agnostic Causally Constrained Counterfactual Generation

Sopam Dasgupta, Sadaf MD Halim, Joaquín Arias, Elmer Salazar, Gopal Gupta; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:926-937

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Neurosymbolic Learning in Structured Probability Spaces: A Case Study

Ole Fenske, Sebastian Bader, Thomas Kirste; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:938-956

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Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systems

Aniruddha Chattopadhyay, Raj Dandekar, Kaushik Roy; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:957-976

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Explainable Zero-Shot Visual Question Answering via Logic-Based Reasoning

Thomas Eiter, Jan Hadl, Nelson Higuera Ruiz, Lukas Lange, Johannes Oetsch, Bileam Scheuvens, Jannik Strötgen; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:977-991

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An evidence-based neuro-symbolic framework for ambiguous image scene classification

Giulia Murtas, Veselka Boeva, Elena Tsiporkova; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:992-1003

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A Neurosymbolic Approach to Counterfactual Fairness

Xenia Heilmann, Chiara Manganini, Mattia Cerrato, Vaishak Belle; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:1004-1025

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Learning Symbolic Persistent Macro-Actions for POMDP Solving Over Time

Celeste Veronese, Daniele Meli, Alessandro Farinelli; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:1026-1040

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KEA Explain: Explanations of Hallucinations using Graph Kernel Analysis

Reilly Haskins, Benjamin Adams; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:1041-1058

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Enhancing Large Language Models with Neurosymbolic Reasoning for Multilingual Tasks

Sina Bagheri Nezhad, Ameeta Agrawal; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:1059-1076

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Object-Centric Neuro-Argumentative Learning

Abdul Rahman Jacob, Avinash Kori, Emanuele De Angelis, Ben Glocker, Maurizio Proietti, Francesca Toni; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:1077-1089

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Neuro-Argumentative Learning with Case-Based Reasoning

Adam Gould, Francesca Toni; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:1090-1106

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Linearithmic Clean-up for Vector-Symbolic Key-Value Memory with Kroneker Rotation Products

Ruipeng Liu, Qinru Qiu, Simon Khan, Garrett Ethan Katz; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:1107-1118

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Evaluating Neuro-Symbolic AI Architectures: Design Principles, Qualitative Benchmark, Comparative Analysis and Results

Oualid BOUGZIME, Samir Jabbar, Christophe Cruz, Frédéric Demoly; Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning, PMLR 284:1119-1143

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