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ORCID4th IJCLR 2024: Nanjing, China
- Wang-Zhou Dai:
Learning and Reasoning - 4th International Joint Conference on Learning and Reasoning, IJCLR 2024, and 33rd International Conference on Inductive Logic Programming, ILP 2024, Nanjing, China, September 20-22, 2024, Proceedings. Lecture Notes in Computer Science 16059, Springer 2026, ISBN 978-3-032-09086-7
Inductive Logic Programming
- Taosheng Qiu, Ryutaro Ichise:
Inventing Recursive Predicates by Sampling and Folding Deduced and Abduced Atoms. 3-18 - Stassa Patsantzis:
From Model-Based Learning to Model-Free Behaviour with Meta-Interpretive Learning. 19-34 - James Trewern, Stassa Patsantzis, Alireza Tamaddoni-Nezhad:
Meta-Interpretive Learning as Second Order Resolution. 35-47 - Dany Varghese, Daniel Cyrus, Stassa Patsantzis, James Trewern, Alfie Anthony Treloar
, Alan Hunter, Alireza Tamaddoni-Nezhad:
One-Shot Learning of Autonomous Behaviour: A Meta Inverse Entailment Approach. 48-65 - Tony Ribeiro, Maxime Folschette, Morgan Magnin, Kotaro Okazaki, Kuo-Yen Lo, Antoine Roquilly, Jérémie Poschmann, Katsumi Inoue:
Learning from Interpretation Transition with Unknowns. 66-85 - Nikolai-Iraj Sanamrad, Cristina Padró-Ferragut, Carlos Monserrat, M. José Ramírez-Quintana:
Towards an Automatic Student Supervisor System Using Declarative Languages. 86-100 - Liao Zhang, David M. Cerna, Cezary Kaliszyk:
Learning Rules Explaining Interactive Theorem Proving Tactic Prediction. 101-116 - Lun Ai, Stephen H. Muggleton, Shi-Shun Liang, Geoff S. Baldwin:
Active Learning of Digenic Functions with Boolean Matrix Logic Programming. 117-125
Learning and Reasoning with Uncertainty
- Nijesh Upreti, Vaishak Belle:
An Algebraic Framework for Hierarchical Probabilistic Abstraction. 129-146 - Stanislaw J. Purgal, David M. Cerna, Cezary Kaliszyk:
Differentiable Inductive Logic Programming in High-Dimensional Space. 147-162 - Yu Jin, Jingming Liu, Zhexu Luo, Yifei Peng, Ziang Qin, Wang-Zhou Dai, Yao-Xiang Ding, Kun Zhou:
Pre-Training Meta-Rule Selection Policy for Visual Generative Abductive Learning. 163-180 - Zahra Chaghazardi, Saber Fallah, Alireza Tamaddoni-Nezhad:
Leveraging Inductive Logic Programming and Deep Learning for Trustworthy Vision. 181-194 - Claude Sammut:
Measurement and Evaluation of Intelligent Robots. 195-202 - Daniel Cyrus, Dany Varghese, Alireza Tamaddoni-Nezhad:
An Inductive Logic Programming Approach for Feature-Range Discovery. 203-217 - Vaishak Belle:
Language-Agnostic Semantics for Implicit Learning as Reasoning: Extended Abstract. 218-227 - Vaishak Belle, Daxin Liu:
Reasoning About Neural Network Perception in the Situation Calculus. 228-237 - Robin Manhaeve, Francesco Giannini, Mehdi Ali, Damiano Azzolini, Alice Bizzarri, Andrea Borghesi, Samuele Bortolotti, Luc De Raedt, Devendra Singh Dhami, Michelangelo Diligenti, Sebastijan Dumancic, Boi Faltings, Elisabetta Gentili, Alfonso Gerevini, Marco Gori, Tias Guns, Martin Homola, Kristian Kersting, Jens Lehmann, Michele Lombardi, Luca Salvatore Lorello, Emanuele Marconato, Stefano Melacci, Andrea Passerini, Debjit Paul, Fabrizio Riguzzi, Stefano Teso, Neil Yorke-Smith, Marco Lippi:
Benchmarking in Neuro-Symbolic AI. 238-249
Formal Reasoning with Large Language Models
- Xue Li, Vaishak Belle, Björn Ross:
MisCC: Misinformation Detection on Counterfactual Claims. 253-267 - Dany Varghese, Ghazal Afroozi Milani, Alireza Tamaddoni-Nezhad:
Towards Enhancing LLMs with Logic-Based Reasoning: A Meta Inverse Entailment Approach. 268-282 - Derian Boer, Fabian Koch, Stefan Kramer:
Harnessing the Power of Semi-structured Knowledge and LLMs with Triplet-Based Prefiltering for Question Answering. 283-292
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