Neurosymbolic Learning

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5 papers in the last four weeks, up 67% on the four weeks before. 0.0% of all new papers.

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DPNL: A DPLL-based Algorithm for Probabilistic Neurosymbolic Learning
Oct 5, 2026Thomas Jean-Michel Valentin, Pierre Genev{è}s, Luisa Sophie Werner +3Probabilistic Logic Neurosymbolic Learning
ENS Paris Saclay,TYREX · LIG,TYREX · TYREX +1
Prototype-Rule Neurosymbolic Regularization for Rank-Constrained Tensor Neural Networks under Label Scarcity
Sep 30, 2026Eftychios Protopapadakis, Konstantinos Makantasis, Konstantinos M. GiannoutakisTensor Networks Prototype Learning
Department of Applied Informatics, University of Macedonia, 156 Egnatia Street, 54636 Thessaloniki, Greece · Department of Artificial Intelligence, Faculty of Information & Communication Technology, University of Malta, Msida, Malta
Candidate Retention for Abductive Learning
Sep 30, 2026Hao-Yuan He, Yu Liu, Ming LiAbductive Reasoning Pseudo-Labeling
School of Artificial Intelligence, Nanjing University · National Key Laboratory for Novel Software Technology, Nanjing University
Neuro-symbolic AI for Industrial Configuration
Sep 24, 2026Danilo Valerio, Philipp Kogler, Stefan Bischof +2Manufacturing Neuro-Symbolic Reasoning
Siemens AG Österreich · Siemens AG
Neurosymbolic Action Model Learning under Partial Observability
Sep 22, 2026Adem Kikaj, Lennert De Smet, Giuseppe Marra +1Symbolic Planning Neurosymbolic Learning
KU Leuven, Belgium
Learning Symbolic Constraint Representations from Examples: A Neuro-Symbolic Approach
Sep 14, 2026Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar +1Symbolic Reasoning Neurosymbolic Learning
Simula Research Laboratory, Oslo, Norway · Microsoft, Norway · LISN, CNRS, Paris-Saclay University, France
Neural Symbollic Regression Using Deep Learning and Sparse Modelling
Sep 1, 2026Ravi Kumar U, Sumitra SScientific ML Neurosymbolic Learning
Department of Mathematics Indian Institute of Space Science and Technology Thiruvananthapuram, India
Reinforcement Learning for Symbolic Equation Solving
Aug 31, 2026Kevin P O KeeffeReinforcement Learning Neurosymbolic Learning
Starling Research Institute
Moose: Latent concept learning with reasoning-shortcut awareness in $\mathcal{EL}^{++}$
Aug 13, 2026Olga Mashkova, Asaad Mohammedsaleh, Fernando Zhapa-Camacho +1Neurosymbolic Learning Description Logic
Computer Science Program, Computer, Electrical, and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning
Aug 4, 2026Agnese Chiatti, Michael Cochez, Cristina Cornelio +14Symbolic Reasoning Neuro-Symbolic Reasoning
Politecnico di Milano · ELLIS Institute Finland & Abo Akademi University · Samsung AI +12
SJEPA: Learning Elegant Latent Dynamics with Hybrid Symbolic-Neural Predictors
Aug 4, 2026Yongchao HuangLatent Dynamics Modeling Joint-Embedding Predictive Architecture
NSMA: Neuro-Symbolic Manifold Alignment for Generalizable Adaptive Bitrate Streaming under Texture Shift
Jul 21, 2026Zhiqiang He, Zhi LiuNeural Network Generalization Domain Generalization
The University of Electro-Communications Tokyo, Japan
Answer Set Programming Energised! End-to-End Neurosymbolic Reasoning and Learning with ASP and Energy Based Models
Jul 9, 2026Jakob Suchan, Julius Monsen, Salim Baloch +1Energy-Based Models Answer Set Programming
Constructor University Bremen, Bremen, Germany · CoDesign Lab > Cognitive Vision · Örebro University, Örebro, Sweden
Differentiate the Evaluator, Not the Program: An Efficient Runtime Representation for Neuro-Symbolic Learning
Jul 3, 2026Lucas ShenemanAutomatic Differentiation Differentiable Programming
Institute for Interdisciplinary Data Sciences University of Idaho
KG-TRACE: A Neuro-Symbolic Framework for Mechanistic Grounding in Antimicrobial Resistance Prediction
Jun 24, 2026Naman Garg, Sarika Jain, Sourav Yadav +4Genomics Neurosymbolic Learning
National Institute of Technology Kurukshetra, Kurukshetra, India · Indian Institute of Information Technology Manipur, Manipur, India · Purdue University, West Lafayette, IN, USA +1
NeSyCat Torch: A Differentiable Tensor Implementation of Categorical Semantics for Neurosymbolic Learning
Jun 17, 2026Daniel Romero Schellhorn, Till Mossakowski, Björn GehrkeNeuro-Symbolic Reasoning Neurosymbolic Learning
University of Osnabrück, Osnabrück, Germany
EM-NeSy: Expectation Maximization for Neurosymbolic Learning
Jun 12, 2026Annegret Seibt, Luc De Raedt, Giuseppe MarraSymbolic Reasoning Expectation-Maximization
Department of Computer Science KU Leuven
Accelerating NeurASP with vectorization and caching
Jun 9, 2026Alexander Philipp Rader, Alessandra RussoAnswer Set Programming Neuro-Symbolic Reasoning
Imperial College London
Neuro-Symbolic Learning for Long-Horizon Task Planning Under Complex Logical Constraints
Jun 5, 2026Qiwei Du, Zitong Zhan, Shaoshu Su +7Symbolic Planning Robot Task Planning
Spatial AI & Robotics (SAIR) Lab, University at Buffalo, NY 14260 · Robotics Institute, Carnegie Mellon University, PA 15213
DisjunctiveNet: Neural Symbolic Learning via Differentiable Convexified Optimization Layers
May 28, 2026Shraman Pal, Can LiDifferentiable Optimization Neurosymbolic Learning
Davidson School of Chemical Engineering, Purdue University, West Lafayette, USA.
Neurosymbolic Learning for Inference-Time Argumentation
May 19, 2026Gabriel Freedman, Adam Dejl, Adam Gould +4Claim Verification Computational Argumentation
Department of Computing, Imperial College London
Learning How to Cube
May 15, 2026Ferhat Erata, Sam Kouteili, Thanos Typaldos +4Transformer Constraint Satisfaction
Yale University · AWS Agentic AI
Quantitative Linear Logic for Neuro-Symbolic Learning and Verification
May 13, 2026Thomas Flinkow, Ekaterina Komendantskaya, Matteo Capucci +1Neural Network Verification Neuro-Symbolic Reasoning
Maynooth University, Maynooth, IE · University of Southampton, Southampton, UK · University of Strathclyde, Glasgow, UK +1
Differentiable Learning of Lifted Action Schemas for Classical Planning
May 13, 2026Jonas Reiter, Jakob Elias Gebler, Hector GeffnerSymbolic Planning Differentiable Programming
RWTH Aachen University
DeepLog: A Software Framework for Modular Neurosymbolic AI
May 11, 2026Robin Manhaeve, Stefano Colamonaco, Vincent Derkinderen +4Neuro-Symbolic AI Neurosymbolic Learning
Department of Computer Science and Leuven.AI KU Leuven, Belgium
From Passive Reuse to Active Reasoning: Grounding Large Language Models for Neuro-Symbolic Experience Replay
May 10, 2026Yanan Xiao, Yixiang Tang, Zechen Feng +3Reinforcement Learning Experience Replay
1Affiliation 1 · 2Affiliation 2 · 3Affiliation 3
Neurosymbolic Imitation Learning with Human Guidance: A Privileged Information Approach
May 8, 2026Nikhilesh Prabhakar, Varun Balaji, Athresh Karanam +2Imitation Learning Neurosymbolic Learning
Department of Computer Science, The University of Texas at Dallas, Richardson TX 75080, USA · Computer Science Department and Centre for Cognitive Science, TU Darmstadt, Germany
LANTERN: LLM-Augmented Neurosymbolic Transfer with Experience-Gated Reasoning Networks
May 6, 2026Mahyar Alinejad, Yue Wang, Amrit Singh Bedi +1Reinforcement Learning LLM-Guided RL
Department of Electrical and Computer Engineering, University of Central Florida, Orlando, Florida, USA · Department of Computer Science, University of Central Florida, Orlando, Florida, USA
Learning to Theorize the World from Observation
May 5, 2026Doojin Baek, Gyubin Lee, Junyeob Baek +2Computational Cognitive Modeling World Model Learning
KAIST
Neural Decision-Propagation for Answer Set Programming
May 3, 2026Thomas Eiter, Katsumi Inoue, Sota MoriyamaAnswer Set Programming Neuro-Symbolic Reasoning
1Vienna University of Technology (TU Wien), Austria · 2National Institute of Informatics, Japan · 3The Graduate University for Advanced Studies, SOKENDAI, Japan

Oct 5, 2026, cs.AIJ/K move · Enter open · S save

DPNL: A DPLL-based Algorithm for Probabilistic Neurosymbolic Learning

Thomas Jean-Michel Valentin, Pierre Genev{è}s, Luisa Sophie Werner, Sarah Chlyah+2

ENS Paris Saclay,TYREX · LIG,TYREX · TYREX+1

Probabilistic Logic Neurosymbolic Learning

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Probabilistic Neurosymbolic Learning (PNL) combines neural predictions with symbolic reasoning, enabling end-to-end learning from final-output supervision without labels for intermediate concepts. A central challenge is probabilistic inference: state-of-the-art approaches often rely on materializing the logical provenance of a query, which can itself become a major computational bottleneck. We introduce Dynamic Probabilistic Neurosymbolic Learning (DPNL), an oracle-guided framework that avoids requiring complete provenance materialization before inference. DPNL lazily explores the space of intermediate assignments, while oracles resolve entire regions that can already be certified to produce or exclude the target output. We establish conditions ensuring soundness and termination. ApproxDPNL extends the same search with early termination while maintaining certified bounds on the exact output probability, providing controlled approximation guarantees. The oracle interface decouples inference from the representation of the symbolic component, enabling problem-specific reasoning within the same framework. Experiments on several neurosymbolic tasks show that DPNL and ApproxDPNL substantially extend the range of problem instances tractable by probabilistic neurosymbolic inference.

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