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An Overview of Machine Teaching

arXiv 1801.05927 ↗First posted 18 Jan 2018cs.LGcited by 63

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Abstract (arXiv)

In this paper we try to organize machine teaching as a coherent set of ideas. Each idea is presented as varying along a dimension. The collection of dimensions then form the problem space of machine teaching, such that existing teaching problems can be characterized in this space. We hope this organization allows us to gain deeper understanding of individual teaching problems, discover connections among them, and identify gaps in the field.

Key facts. Cited by 63 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Jan 2018.

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Citing papers per year: 2018: 1; 2019: 2; 2020: 1; 2021: 13; 2022: 11; 2023: 12; 2024: 11; 2025: 6; 2026: 6.

63 papers.

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  1. 2022Sample Efficient Learning of Predictors that Complement Humanscited by 46
  2. 2021Teaching Humans When To Defer to a Classifier via Exemplarscited by 29
  3. 2018Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applicationscited by 28
  4. 2021Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environmentscited by 26
  5. 2021Reinforcement Learning for Education: Opportunities and Challengescited by 25
  6. 2019Interactive Teaching Algorithms for Inverse Reinforcement Learningcited by 24
  7. 2023Proximal Curriculum for Reinforcement Learning Agentscited by 19
  8. 2019Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraintscited by 18
  9. 2025Optimal Task Order for Continual Learning of Multiple Taskscited by 14
  10. 2024Nonparametric Teaching of Implicit Neural Representationscited by 13
  11. 2021Teaching an Active Learner with Contrastive Examplescited by 12
  12. 2024Toward In-Context Teaching: Adapting Examples to Students' Misconceptionscited by 12
38 more
  1. 2021Fair Clustering Using Antidote Datacited by 10
  2. 2021Iterative Teaching by Label Synthesiscited by 10
  3. 2021Curriculum Design for Teaching via Demonstrations: Theory and Applicationscited by 9
  4. 2023Nonparametric Iterative Machine Teachingcited by 9
  5. 2022Iterative Teaching by Data Hallucinationcited by 8
  6. 2023How To Guide Your Learner: Imitation Learning with Active Adaptive Expert Involvementcited by 8
  7. 2023Towards Effective Human-AI Decision-Making: The Role of Human Learning in Appropriate Reliance on AI Advicecited by 8
  8. 2024Clarify: Improving Model Robustness With Natural Language Correctionscited by 8
  9. 2023Nonparametric Teaching for Multiple Learnerscited by 7
  10. 2022Reasoning about Counterfactuals to Improve Human Inverse Reinforcement Learningcited by 6
  11. 2022Blind Users Accessing Their Training Images in Teachable Object Recognizerscited by 6
  12. 2024Proximal Curriculum with Task Correlations for Deep Reinforcement Learningcited by 6
  13. 2024Computational Teaching for Driving via Multi-Task Imitation Learningcited by 6
  14. 2023Non-Clashing Teaching Maps for Balls in Graphscited by 5
  15. 2024Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Studycited by 5
  16. 2025Nonparametric Teaching for Graph Property Learnerscited by 5
  17. 2021Exploring Machine Teaching with Childrencited by 4
  18. 2021Agent Smith: Teaching Question Answering to Jill Watsoncited by 4
  19. 2023Learning Human-Compatible Representations for Case-Based Decision Supportcited by 4
  20. 2023ML-Based Teaching Systems: A Conceptual Frameworkcited by 3
  21. 2024Transferring Domain Knowledge with (X)AI-Based Learning Systemscited by 3
  22. 2024Representational Alignment Supports Effective Machine Teachingcited by 3
  23. 2025Interaction-Driven Browsing: A Human-in-the-Loop Conceptual Framework Informed by Human Web Browsing for Browser-Using Agentscited by 3
  24. 2023Multi-Agent Strategy Explanations for Human-Robot Collaborationcited by 2
  25. 2024When Redundancy Matters: Machine Teaching of Representationscited by 2
  26. 2025The Computational Complexity of Positive Non-Clashing Teaching in Graphscited by 2
  27. 2021Distribution Matching for Machine Teachingcited by 1
  28. 2022Time-Constrained Learningcited by 1
  29. 2022Reinforcement Teachingcited by 1
  30. 2022Human-AI Interaction Design in Machine Teachingcited by 1
  31. 2022Black-box Generalization of Machine Teachingcited by 1
  32. 2022Visual Knowledge Tracingcited by 1
  33. 2023MAP- and MLE-Based Teachingcited by 1
  34. 2023Utility-based Adaptive Teaching Strategies using Bayesian Theory of Mindcited by 1
  35. 2024Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning Modelscited by 1
  36. 2026Nonparametric Teaching of Attention Learnerscited by 1
  37. 2020Interaction-limited Inverse Reinforcement Learningcited by 0
  38. 2021CACTUS: Detecting and Resolving Conflicts in Objective Functionscited by 0

50 most cited of 63 All 63 (JSON)