{"total":225,"rows":[{"id":"2206.00426","title":"Semantic Probabilistic Layers for Neuro-Symbolic Learning","created":"2022-06-01","cited_by_count":103,"area":null},{"id":"2307.07700","title":"NeurASP: Embracing Neural Networks into Answer Set Programming","created":"2023-07-15","cited_by_count":92,"area":null},{"id":"2112.13112","title":"A Survey on Interpretable Reinforcement Learning","created":"2021-12-24","cited_by_count":73,"area":null},{"id":"2108.11451","title":"From Statistical Relational to Neurosymbolic Artificial Intelligence: a Survey","created":"2021-08-25","cited_by_count":72,"area":null},{"id":"2305.19951","title":"Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts","created":"2023-05-31","cited_by_count":63,"area":null},{"id":"2103.00180","title":"Incorporating Domain Knowledge into Deep Neural Networks","created":"2021-02-27","cited_by_count":56,"area":null},{"id":"2105.05330","title":"Neuro-Symbolic Artificial Intelligence: Current Trends","created":"2021-05-11","cited_by_count":54,"area":null},{"id":"2307.01717","title":"On the Constrained Time-Series Generation Problem","created":"2023-07-04","cited_by_count":54,"area":null},{"id":"2111.01564","title":"MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks","created":"2021-11-02","cited_by_count":44,"area":null},{"id":"2205.00523","title":"Deep Learning with Logical Constraints","created":"2022-05-01","cited_by_count":44,"area":null},{"id":"2103.05134","title":"Constrained Learning with Non-Convex Losses","created":"2021-03-08","cited_by_count":42,"area":null},{"id":"2303.03226","title":"Safe Reinforcement Learning via Probabilistic Logic Shields","created":"2023-03-06","cited_by_count":42,"area":null},{"id":"2102.11965","title":"Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases","created":"2021-02-23","cited_by_count":39,"area":null},{"id":"2111.08164","title":"A Survey on Neural-symbolic Learning Systems","created":"2021-11-10","cited_by_count":39,"area":null},{"id":"2402.12240","title":"BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts","created":"2024-02-19","cited_by_count":37,"area":null},{"id":"2103.13427","title":"Multi-Label Classification Neural Networks with Hard Logical Constraints","created":"2021-03-24","cited_by_count":36,"area":null},{"id":"2104.01396","title":"Neural Network Robustness as a Verification Property: A Principled Case Study","created":"2021-04-03","cited_by_count":35,"area":null},{"id":"2210.15889","title":"Towards Data-and Knowledge-Driven Artificial Intelligence: A Survey on Neuro-Symbolic Computing","created":"2022-10-28","cited_by_count":35,"area":null},{"id":"2210.01597","title":"ROAD-R: The Autonomous Driving Dataset with Logical Requirements","created":"2022-10-04","cited_by_count":34,"area":null},{"id":"2210.01941","title":"SIMPLE: A Gradient Estimator for $k$-Subset Sampling","created":"2022-10-04","cited_by_count":34,"area":null},{"id":"2210.08465","title":"Character-Centric Story Visualization via Visual Planning and Token Alignment","created":"2022-10-16","cited_by_count":33,"area":null},{"id":"2302.01242","title":"Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal","created":"2023-02-02","cited_by_count":33,"area":null},{"id":"2410.10807","title":"HardNet: Hard-Constrained Neural Networks with Universal Approximation Guarantees","created":"2024-10-14","cited_by_count":31,"area":null},{"id":"2104.11914","title":"EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case","created":"2021-04-24","cited_by_count":30,"area":null},{"id":"2409.13724","title":"Logically Consistent Language Models via Neuro-Symbolic Integration","created":"2024-09-09","cited_by_count":30,"area":null},{"id":"2308.12595","title":"Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentation","created":"2023-08-24","cited_by_count":29,"area":null},{"id":"2402.04823","title":"How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data","created":"2024-02-07","cited_by_count":29,"area":null},{"id":"2304.13188","title":"TABLET: Learning From Instructions For Tabular Data","created":"2023-04-25","cited_by_count":28,"area":null},{"id":"2201.11250","title":"Neuro-Symbolic Entropy Regularization","created":"2022-01-25","cited_by_count":27,"area":null},{"id":"2303.04660","title":"Neural Probabilistic Logic Programming in Discrete-Continuous Domains","created":"2023-03-08","cited_by_count":25,"area":null},{"id":"2311.09817","title":"Neural-Logic Human-Object Interaction Detection","created":"2023-11-16","cited_by_count":25,"area":null},{"id":"2406.00766","title":"Scaling Tractable Probabilistic Circuits: A Systems Perspective","created":"2024-06-02","cited_by_count":23,"area":null},{"id":"2312.03905","title":"A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints","created":"2023-12-06","cited_by_count":22,"area":null},{"id":"2307.04895","title":"Learning to Solve Constraint Satisfaction Problems with Recurrent Transformer","created":"2023-07-10","cited_by_count":21,"area":null},{"id":"2406.10368","title":"A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcuts","created":"2024-06-14","cited_by_count":19,"area":null},{"id":"2404.08458","title":"On the Independence Assumption in Neurosymbolic Learning","created":"2024-04-12","cited_by_count":18,"area":null},{"id":"2409.13456","title":"Concept-Based Explanations in Computer Vision: Where Are We and Where Could We Go?","created":"2024-09-20","cited_by_count":18,"area":null},{"id":"2502.18237","title":"Beyond the convexity assumption: Realistic tabular data generation under quantifier-free real linear constraints","created":"2025-02-25","cited_by_count":18,"area":null},{"id":"2309.13556","title":"LOGICSEG: Parsing Visual Semantics with Neural Logic Learning and Reasoning","created":"2023-09-24","cited_by_count":17,"area":null},{"id":"2407.15527","title":"Interpretable Concept-Based Memory Reasoning","created":"2024-07-22","cited_by_count":17,"area":null},{"id":"2110.09383","title":"Neuro-Symbolic Forward Reasoning","created":"2021-10-18","cited_by_count":16,"area":null},{"id":"2403.00323","title":"Softened Symbol Grounding for Neuro-symbolic Systems","created":"2024-03-01","cited_by_count":16,"area":null},{"id":"2410.11415","title":"KLay: Accelerating Arithmetic Circuits for Neurosymbolic AI","created":"2024-10-15","cited_by_count":16,"area":null},{"id":"2106.13103","title":"FF-NSL: Feed-Forward Neural-Symbolic Learner","created":"2021-06-24","cited_by_count":15,"area":null},{"id":"2303.10650","title":"Logic of Differentiable Logics: Towards a Uniform Semantics of DL","created":"2023-03-19","cited_by_count":15,"area":null},{"id":"2304.08349","title":"Deep Explainable Relational Reinforcement Learning: A Neuro-Symbolic Approach","created":"2023-04-17","cited_by_count":15,"area":null},{"id":"2205.07548","title":"A Neuro-Symbolic ASP Pipeline for Visual Question Answering","created":"2022-05-16","cited_by_count":14,"area":null},{"id":"2306.13796","title":"On Learning Latent Models with Multi-Instance Weak Supervision","created":"2023-06-23","cited_by_count":13,"area":null},{"id":"2502.11245","title":"Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens","created":"2025-02-16","cited_by_count":13,"area":null},{"id":"2108.12370","title":"DomiKnowS: A Library for Integration of Symbolic Domain Knowledge in Deep Learning","created":"2021-08-27","cited_by_count":12,"area":null},{"id":"2205.12735","title":"Neuro-Symbolic Learning of Answer Set Programs from Raw Data","created":"2022-05-25","cited_by_count":12,"area":null},{"id":"2302.14207","title":"Semantic Strengthening of Neuro-Symbolic Learning","created":"2023-02-28","cited_by_count":12,"area":null},{"id":"2307.04347","title":"Injecting Logical Constraints into Neural Networks via Straight-Through Estimators","created":"2023-07-10","cited_by_count":12,"area":null},{"id":"2103.17232","title":"Neuro-Symbolic Constraint Programming for Structured Prediction","created":"2021-03-31","cited_by_count":11,"area":null},{"id":"2206.04976","title":"Refining neural network predictions using background knowledge","created":"2022-06-10","cited_by_count":11,"area":null},{"id":"2410.13111","title":"Controllable Generation via Locally Constrained Resampling","created":"2024-10-17","cited_by_count":11,"area":null},{"id":"2503.19466","title":"A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction","created":"2025-03-25","cited_by_count":11,"area":null},{"id":"2105.14146","title":"Deep Fair Discriminative Clustering","created":"2021-05-28","cited_by_count":10,"area":null},{"id":"2212.00017","title":"Knowledge-augmented Deep Learning and Its Applications: A Survey","created":"2022-11-30","cited_by_count":10,"area":null},{"id":"2403.00329","title":"Learning with Logical Constraints but without Shortcut Satisfaction","created":"2024-03-01","cited_by_count":10,"area":null},{"id":"2411.04383","title":"Neuro-Symbolic AI: Explainability, Challenges, and Future Trends","created":"2024-11-07","cited_by_count":10,"area":null},{"id":"2102.10865","title":"Handling Epistemic and Aleatory Uncertainties in Probabilistic Circuits","created":"2021-02-22","cited_by_count":9,"area":null},{"id":"2108.09523","title":"Automating Crystal-Structure Phase Mapping: Combining Deep Learning with Constraint Reasoning","created":"2021-08-21","cited_by_count":9,"area":null},{"id":"2202.02942","title":"Tractable Boolean and Arithmetic Circuits","created":"2022-02-07","cited_by_count":9,"area":null},{"id":"2302.10914","title":"GLUECons: A Generic Benchmark for Learning Under Constraints","created":"2023-02-16","cited_by_count":9,"area":null},{"id":"2311.13718","title":"A Unified Approach to Count-Based Weakly-Supervised Learning","created":"2023-11-22","cited_by_count":9,"area":null},{"id":"2403.11348","title":"COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits","created":"2024-03-17","cited_by_count":9,"area":null},{"id":"2405.00532","title":"ULLER: A Unified Language for Learning and Reasoning","created":"2024-05-01","cited_by_count":9,"area":null},{"id":"2406.12147","title":"Metacognitive AI: Framework and the Case for a Neurosymbolic Approach","created":"2024-06-17","cited_by_count":9,"area":null},{"id":"2106.01809","title":"Exploring Distantly-Labeled Rationales in Neural Network Models","created":"2021-06-03","cited_by_count":8,"area":null},{"id":"2107.13646","title":"Evaluating Relaxations of Logic for Neural Networks: A Comprehensive Study","created":"2021-07-28","cited_by_count":8,"area":null},{"id":"2109.01634","title":"AI Descartes: Combining Data and Theory for Derivable Scientific Discovery","created":"2021-09-03","cited_by_count":8,"area":null},{"id":"2304.03674","title":"Machine Learning with Requirements: a Manifesto","created":"2023-04-07","cited_by_count":8,"area":null},{"id":"2304.11357","title":"Learning Symbolic Representations Through Joint GEnerative and DIscriminative Training","created":"2023-04-22","cited_by_count":8,"area":null},{"id":"2404.19696","title":"Naturally Supervised 3D Visual Grounding with Language-Regularized Concept Learners","created":"2024-04-30","cited_by_count":8,"area":null},{"id":"2507.11127","title":"Defining neurosymbolic AI","created":"2025-07-15","cited_by_count":8,"area":null},{"id":"2102.06137","title":"A Compositional Atlas of Tractable Circuit Operations: From Simple Transformations to Complex Information-Theoretic Queries","created":"2021-02-11","cited_by_count":7,"area":null},{"id":"2112.15319","title":"A Critical Review of Inductive Logic Programming Techniques for Explainable AI","created":"2021-12-31","cited_by_count":7,"area":null},{"id":"2208.00374","title":"Neuro-Symbolic Learning: Principles and Applications in Ophthalmology","created":"2022-07-31","cited_by_count":7,"area":null},{"id":"2406.06246","title":"Data-Efficient Learning with Neural Programs","created":"2024-06-10","cited_by_count":7,"area":null},{"id":"2407.15192","title":"Error Detection and Constraint Recovery in Hierarchical Multi-Label Classification without Prior Knowledge","created":"2024-07-21","cited_by_count":7,"area":null},{"id":"2509.01398","title":"The Need for Verification in AI-Driven Scientific Discovery","created":"2025-09-01","cited_by_count":7,"area":null},{"id":"2105.10709","title":"Inclusion of Domain-Knowledge into GNNs using Mode-Directed Inverse Entailment","created":"2021-05-22","cited_by_count":6,"area":null},{"id":"2205.09067","title":"Automatic Rule Induction for Interpretable Semi-Supervised Learning","created":"2022-05-18","cited_by_count":6,"area":null},{"id":"2212.13425","title":"GEDI: GEnerative and DIscriminative Training for Self-Supervised Learning","created":"2022-12-27","cited_by_count":6,"area":null},{"id":"2306.09686","title":"Collapsed Inference for Bayesian Deep Learning","created":"2023-06-16","cited_by_count":6,"area":null},{"id":"2311.06673","title":"Dream to Adapt: Meta Reinforcement Learning by Latent Context Imagination and MDP Imagination","created":"2023-11-11","cited_by_count":6,"area":null},{"id":"2408.08133","title":"EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic","created":"2024-08-15","cited_by_count":6,"area":null},{"id":"2107.07696","title":"Constrained Feedforward Neural Network Training via Reachability Analysis","created":"2021-07-16","cited_by_count":5,"area":null},{"id":"2204.09183","title":"Robustness Testing of Data and Knowledge Driven Anomaly Detection in Cyber-Physical Systems","created":"2022-04-20","cited_by_count":5,"area":null},{"id":"2210.14905","title":"RulE: Knowledge Graph Reasoning with Rule Embedding","created":"2022-10-24","cited_by_count":5,"area":null},{"id":"2403.17853","title":"Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic","created":"2024-03-26","cited_by_count":5,"area":null},{"id":"2410.16170","title":"Learning How to Vote with Principles: Axiomatic Insights Into the Collective Decisions of Neural Networks","created":"2024-10-21","cited_by_count":5,"area":null},{"id":"2503.18213","title":"A Study on Neuro-Symbolic Artificial Intelligence: Healthcare Perspectives","created":"2025-03-23","cited_by_count":5,"area":null},{"id":"2508.13697","title":"The DeepLog Neurosymbolic Machine","created":"2025-08-19","cited_by_count":5,"area":null},{"id":"2104.06365","title":"Neuro-Symbolic VQA: A review from the perspective of AGI desiderata","created":"2021-04-13","cited_by_count":4,"area":null},{"id":"2106.00393","title":"Relational Reasoning Networks","created":"2021-06-01","cited_by_count":4,"area":null},{"id":"2106.03121","title":"End-to-End Neuro-Symbolic Architecture for Image-to-Image Reasoning Tasks","created":"2021-06-06","cited_by_count":4,"area":null},{"id":"2303.01141","title":"DeepSaDe: Learning Neural Networks that Guarantee Domain Constraint Satisfaction","created":"2023-03-02","cited_by_count":4,"area":null},{"id":"2311.11208","title":"LogicNet: A Logical Consistency Embedded Face Attribute Learning Network","created":"2023-11-19","cited_by_count":4,"area":null}],"next_cursor":"100"}