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Coherent Hierarchical Multi-Label Classification Networks

arXiv 2010.10151 ↗First posted 20 Oct 2020cs.LG stat.MLcited by 65

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Abstract (arXiv)

Hierarchical multi-label classification (HMC) is a challenging classification task extending standard multi-label classification problems by imposing a hierarchy constraint on the classes. In this paper, we propose C-HMCNN(h), a novel approach for HMC problems, which, given a network h for the underlying multi-label classification problem, exploits the hierarchy information in order to produce predictions coherent with the constraint and improve performance. We conduct an extensive experimental analysis showing the superior performance of C-HMCNN(h) when compared to state-of-the-art models.

Key facts. Cited by 65 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Oct 2020.

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Citing papers per year: 2021: 4; 2022: 13; 2023: 12; 2024: 15; 2025: 11; 2026: 10.

65 papers.

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  1. 2022Semantic Probabilistic Layers for Neuro-Symbolic Learningcited by 103
  2. 2022Deep Hierarchical Semantic Segmentationcited by 84
  3. 2024A Survey of Multimodal Large Language Model from A Data-centric Perspectivecited by 75
  4. 2023Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcutscited by 63
  5. 2022Use All The Labels: A Hierarchical Multi-Label Contrastive Learning Frameworkcited by 59
  6. 2022Deep Learning with Logical Constraintscited by 44
  7. 2024BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcutscited by 37
  8. 2021Multi-Label Classification Neural Networks with Hard Logical Constraintscited by 36
  9. 2023Youku-mPLUG: A 10 Million Large-scale Chinese Video-Language Dataset for Pre-training and Benchmarkscited by 36
  10. 2022Towards Data-and Knowledge-Driven Artificial Intelligence: A Survey on Neuro-Symbolic Computingcited by 35
  11. 2022ROAD-R: The Autonomous Driving Dataset with Logical Requirementscited by 34
  12. 2023Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsalcited by 33
38 more
  1. 2024HardNet: Hard-Constrained Neural Networks with Universal Approximation Guaranteescited by 31
  2. 2024Logically Consistent Language Models via Neuro-Symbolic Integrationcited by 30
  3. 2022Label Relation Graphs Enhanced Hierarchical Residual Network for Hierarchical Multi-Granularity Classificationcited by 29
  4. 2023Interpretability is in the Mind of the Beholder: A Causal Framework for Human-interpretable Representation Learningcited by 22
  5. 2023A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraintscited by 22
  6. 2023LOGICSEG: Parsing Visual Semantics with Neural Logic Learning and Reasoningcited by 17
  7. 2024KLay: Accelerating Arithmetic Circuits for Neurosymbolic AIcited by 16
  8. 2025Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lenscited by 13
  9. 2023Semantic Strengthening of Neuro-Symbolic Learningcited by 12
  10. 2025A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfactioncited by 11
  11. 2023Geometric Relational Embeddings: A Surveycited by 9
  12. 2024Metacognitive AI: Framework and the Case for a Neurosymbolic Approachcited by 9
  13. 2022Hierarchical Interdisciplinary Topic Detection Model for Research Proposal Classificationcited by 8
  14. 2022A Survey of Neural Treescited by 7
  15. 2023Recent Advances in Hierarchical Multi-label Text Classification: A Surveycited by 6
  16. 2021Wallpaper Texture Generation and Style Transfer Based on Multi-label Semanticscited by 4
  17. 2023Multi-Granularity Archaeological Dating of Chinese Bronze Dings Based on a Knowledge-Guided Relation Graphcited by 4
  18. 2021Image Classification with Consistent Supporting Evidencecited by 3
  19. 2021Label Hierarchy Transition: Delving into Class Hierarchies to Enhance Deep Classifierscited by 3
  20. 2022All Mistakes Are Not Equal: Comprehensive Hierarchy Aware Multi-label Predictions (CHAMP)cited by 3
  21. 2024Learning Label Hierarchy with Supervised Contrastive Learningcited by 3
  22. 2024Semantic Loss Functions for Neuro-Symbolic Structured Predictioncited by 3
  23. 2025Leveraging Taxonomy and LLMs for Improved Multimodal Hierarchical Classificationcited by 3
  24. 2025Right for the Right Reasons: Avoiding Reasoning Shortcuts via Prototypical Neurosymbolic AIcited by 3
  25. 2022Efficient and Reliable Probabilistic Interactive Learning with Structured Outputscited by 2
  26. 2024Improving Neural-based Classification with Logical Background Knowledgecited by 2
  27. 2024PiShield: A PyTorch Package for Learning with Requirementscited by 2
  28. 2024Informed deep hierarchical classification: a non-standard analysis inspired approachcited by 2
  29. 2025Factor Graph-based Interpretable Neural Networkscited by 2
  30. 2026Conflict-Free Policy Languages for Probabilistic ML Predicates: A Framework and Case Study with the Semantic Router DSLcited by 2
  31. 2023DOST -- Domain Obedient Self-supervised Training for Multi Label Classification with Noisy Labelscited by 1
  32. 2024Hierarchical Insights: Exploiting Structural Similarities for Reliable 3D Semantic Segmentationcited by 1
  33. 2024Hierarchical Multi-Label Classification with Missing Information for Benthic Habitat Imagerycited by 1
  34. 2025Cross-Hierarchical Bidirectional Consistency Learning for Fine-Grained Visual Classificationcited by 1
  35. 2026Concise and Logically Consistent Conformal Sets for Neuro-Symbolic Concept-Based Modelscited by 1
  36. 2022Ranking hierarchical multi-label classification results with mLPRscited by 0
  37. 2022Semantic Guided Level-Category Hybrid Prediction Network for Hierarchical Image Classificationcited by 0
  38. 2023TLMCM Network for Medical Image Hierarchical Multi-Label Classificationcited by 0

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