Data to 14 Oct 2026

Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets

arXiv 1705.10479 ↗First posted 30 May 2017cs.RO cs.LGcited by 64

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Cited by 43 in Offline RL and imitation learning from data, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Imitation learning has traditionally been applied to learn a single task from demonstrations thereof. The requirement of structured and isolated demonstrations limits the scalability of imitation learning approaches as they are difficult to apply to real-world scenarios, where robots have to be able to execute a multitude of tasks. In this paper, we propose a multi-modal imitation learning framework that is able to segment and imitate skills from unlabelled and unstructured demonstrations by learning skill segmentation and imitation learning jointly. The extensive simulation results indicate that our method can efficiently separate the demonstrations into individual skills and learn to imitate them using a single multi-modal policy. The video of our experiments is available at http://sites.google.com/view/nips17intentiongan

Key facts. Cited by 64 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 May 2017.

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Citing papers per year: 2018: 8; 2019: 8; 2020: 3; 2021: 10; 2022: 10; 2023: 5; 2024: 8; 2025: 6; 2026: 6.

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2022Behavior Transformers: Cloning k modes with one stonecited by 304
20243D Diffuser Actor: Policy Diffusion with 3D Scene Representationscited by 282
2021MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scalecited by 229
2020Language Conditioned Imitation Learning over Unstructured Datacited by 209
2019Imitation Learning via Off-Policy Distribution Matchingcited by 183
2019Imitation Learning as f-Divergence Minimizationcited by 123
2019Meta-Inverse Reinforcement Learning with Probabilistic Context Variablescited by 50
2022Imitation Learning by Estimating Expertise of Demonstratorscited by 50
2021Visual Adversarial Imitation Learning using Variational Modelscited by 42
2021Learning Multimodal Rewards from Rankingscited by 41
2018Learning a Prior over Intent via Meta-Inverse Reinforcement Learningcited by 36
2018Sample-Efficient Imitation Learning via Generative Adversarial Netscited by 36

38 more

2018One-Shot Hierarchical Imitation Learning of Compound Visuomotor Taskscited by 33
2018Generative Adversarial Self-Imitation Learningcited by 25
2021MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learningcited by 25
2022Eliciting Compatible Demonstrations for Multi-Human Imitation Learningcited by 23
2018Multi-task Maximum Entropy Inverse Reinforcement Learningcited by 20
2022An Independently Learnable Hierarchical Model for Bilateral Control-Based Imitation Learning Applicationscited by 14
2024STEER: Flexible Robotic Manipulation via Dense Language Groundingcited by 14
2021Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Taskscited by 13
2019VILD: Variational Imitation Learning with Diverse-quality Demonstrationscited by 12
2018Maximum Causal Tsallis Entropy Imitation Learningcited by 10
2022Learning from Guided Play: Improving Exploration for Adversarial Imitation Learning with Simple Auxiliary Taskscited by 10
2025Learning Coordinated Bimanual Manipulation Policies using State Diffusion and Inverse Dynamics Modelscited by 9
2025Intention-Conditioned Flow Occupancy Modelscited by 9
2025VFP: Variational Flow-Matching Policy for Multi-Modal Robot Manipulationcited by 9
2018CompILE: Compositional Imitation Learning and Executioncited by 7
2019Integration of Imitation Learning using GAIL and Reinforcement Learning using Task-achievement Rewards via Probabilistic Graphical Modelcited by 7
2024Crowd-PrefRL: Preference-Based Reward Learning from Crowdscited by 7
2021Deep Adaptive Multi-Intention Inverse Reinforcement Learningcited by 6
2022SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisitioncited by 6
2022ASE: Large-Scale Reusable Adversarial Skill Embeddings for Physically Simulated Characterscited by 6
2022Diverse Imitation Learning via Self-Organizing Generative Modelscited by 5
2023Learning Models of Adversarial Agent Behavior under Partial Observabilitycited by 5
2024IDIL: Imitation Learning of Intent-Driven Expert Behaviorcited by 5
2019Situated GAIL: Multitask imitation using task-conditioned adversarial inverse reinforcement learningcited by 4
2021Learning without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learningcited by 4
2024Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learningcited by 4
2020oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actionscited by 3
2021Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learningcited by 3
2023Curriculum-Based Imitation of Versatile Skillscited by 3
2023Hierarchical Imitation Learning for Stochastic Environmentscited by 3
2020Generalization Guarantees for Imitation Learningcited by 2
2022Modular Adaptive Policy Selection for Multi-Task Imitation Learning through Task Divisioncited by 2
2024Navigation with QPHIL: Quantizing Planner for Hierarchical Implicit Q-Learningcited by 2
2025Hierarchical Imitation Learning of Team Behavior from Heterogeneous Demonstrationscited by 2
2025Offline Learning of Controllable Diverse Behaviorscited by 2
2026CoMI-IRL: Contrastive Multi-Intention Inverse Reinforcement Learningcited by 2
2026A Generalized Apprenticeship Learning Framework for Capturing Evolving Student Pedagogical Strategiescited by 2
2026Behavioral Mode Discovery for Fine-tuning Multimodal Generative Policiescited by 2

50 most cited of 64 All 64 (JSON)