mlsanityData to 7 Oct 2026

QueST: Self-Supervised Skill Abstractions for Learning Continuous Control

arXiv 2407.15840 ↗First posted 22 Jul 2024cs.ROcited by 51

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Abstract (arXiv)

Generalization capabilities, or rather a lack thereof, is one of the most important unsolved problems in the field of robot learning, and while several large scale efforts have set out to tackle this problem, unsolved it remains. In this paper, we hypothesize that learning temporal action abstractions using latent variable models (LVMs), which learn to map data to a compressed latent space and back, is a promising direction towards low-level skills that can readily be used for new tasks. Although several works have attempted to show this, they have generally been limited by architectures that do not faithfully capture shareable representations. To address this we present Quantized Skill Transformer (QueST), which learns a larger and more flexible latent encoding that is more capable of modeling the breadth of low-level skills necessary for a variety of tasks. To make use of this extra flexibility, QueST imparts causal inductive bias from the action sequence data into the latent space, leading to more semantically useful and transferable representations. We compare to state-of-the-art imitation learning and LVM baselines and see that QueST's architecture leads to strong performance on several multitask and few-shot learning benchmarks. Further results and videos are available at https://quest-model.github.io/

Key facts. Cited by 51 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Jul 2024.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 27; 2026: 21.

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  1. 2025FAST: Efficient Action Tokenization for Vision-Language-Action Modelscited by 643
  2. 2025UniVLA: Learning to Act Anywhere with Task-centric Latent Actionscited by 386
  3. 2024Latent Action Pretraining from Videoscited by 302
  4. 2025DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledgecited by 203
  5. 2025Real-Time Execution of Action Chunking Flow Policiescited by 199
  6. 2025Interactive Post-Training for Vision-Language-Action Modelscited by 129
  7. 2025Universal Actions for Enhanced Embodied Foundation Modelscited by 80
  8. 2025Training Strategies for Efficient Embodied Reasoningcited by 53
  9. 2024Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learningcited by 46
  10. 2025SoFar: Language-Grounded Orientation Bridges Spatial Reasoning and Object Manipulationcited by 46
  11. 2025SemanticVLA: Semantic-Aligned Sparsification and Enhancement for Efficient Robotic Manipulationcited by 20
  12. 2025Dexterous Manipulation through Imitation Learning: A Surveycited by 18
38 more
  1. 2025AMPLIFY: Actionless Motion Priors for Robot Learning from Videoscited by 18
  2. 2026ActionCodec: What Makes for Good Action Tokenizerscited by 17
  3. 2025Curating Demonstrations using Online Experiencecited by 16
  4. 2025Adapt3R: Adaptive 3D Scene Representation for Domain Transfer in Imitation Learningcited by 16
  5. 2025XR-1: Towards Versatile Vision-Language-Action Models via Learning Unified Vision-Motion Representationscited by 15
  6. 2026AtomicVLA: Unlocking the Potential of Atomic Skill Learning in Robotscited by 15
  7. 2025Balancing Signal and Variance: Adaptive Offline RL Post-Training for VLA Flow Modelscited by 14
  8. 2026OAT: Ordered Action Tokenizationcited by 14
  9. 2025STAR: Learning Diverse Robot Skill Abstractions through Rotation-Augmented Vector Quantizationcited by 13
  10. 2024RoCoDA: Counterfactual Data Augmentation for Data-Efficient Robot Learning from Demonstrationscited by 12
  11. 2025EmbodiedVSR: Dynamic Scene Graph-Guided Chain-of-Thought Reasoning for Visual Spatial Taskscited by 9
  12. 2025SPECI: Skill Prompts based Hierarchical Continual Imitation Learning for Robot Manipulationcited by 9
  13. 2025Continual Learning for Generative AI: From LLMs to MLLMs and Beyondcited by 9
  14. 2026UniT: Toward a Unified Physical Language for Human-to-Humanoid Policy Learning and World Modelingcited by 9
  15. 2025Quantization-Free Autoregressive Action Transformercited by 5
  16. 2026Mimic Intent, Not Just Trajectoriescited by 5
  17. 2025Self-evolved Imitation Learning in Simulated Worldcited by 4
  18. 2026DreamProver: Evolving Transferable Lemma Libraries via a Wake-Sleep Theorem-Proving Agentcited by 4
  19. 2025The Temporal Trap: Entanglement in Pre-Trained Visual Representations for Visuomotor Policy Learningcited by 3
  20. 2025Robotic Manipulation via Imitation Learning: Taxonomy, Evolution, Benchmark, and Challengescited by 3
  21. 2026Learning Diffusion Policy from Primitive Skills for Robot Manipulationcited by 3
  22. 2026MOTIF: Learning Action Motifs for Few-shot Cross-Embodiment Transfercited by 3
  23. 2025Masked Generative Policy for Robotic Controlcited by 2
  24. 2025Learning Skills from Action-Free Videoscited by 2
  25. 2026From Pixels to Tokens: A Systematic Study of Latent Action Supervision for Vision-Language-Action Modelscited by 2
  26. 2026From Imagined Futures to Executable Actions: Mixture of Latent Actions for Robot Manipulationcited by 2
  27. 2026Flowing With Purpose: Latent Action Guided Flow Matching Policies For Robotic Manipulationcited by 2
  28. 2026SUREFlow: State-space Uncertainty-aware REsidual Flow Matching for Robust Robot Manipulationcited by 2
  29. 2026Ordered Action Tokens for Visuomotor Policy Learningcited by 2
  30. 2025Boosting Robotic Manipulation Generalization with Minimal Costly Datacited by 1
  31. 2025Offline Reinforcement Learning with Discrete Diffusion Skillscited by 1
  32. 2026Task-Aware Exploration via a Predictive Bisimulation Metriccited by 1
  33. 2026KineVLA: Towards Kinematics-Aware Vision-Language-Action Models with Bi-Level Action Decompositioncited by 1
  34. 2026Primary-Fine Decoupling for Action Generation in Robotic Imitationcited by 0
  35. 2026Understanding Behavior Cloning with Action Quantizationcited by 0
  36. 2026COBALT: Crowdsourcing Robot Learning via Cloud-Based Teleoperation with Smartphonescited by 0
  37. 2026BooST: Bridging Semantics and Motions for Efficient Skill Transfercited by 0
  38. 2026GaussVLA: Geometry-Aware Spatial Reasoning for Vision-Language-Action Modelcited by 0

50 most cited of 51 All 51 (JSON)

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  1. 2022Learning and Retrieval from Prior Data for Skill-based Imitation Learning
  2. 2025Latent Action Pretraining Through World Modeling
  3. 2024PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
  4. 2026ARP: Enhancing Quantized Skill Abstractions via Visual Alignment and Iterative Refinement for Robotic Manipulation ↗
  5. 2026CARE: Multi-Task Pretraining for Latent Continuous Action Representation in Robot Control
  6. 2022Latent Plans for Task-Agnostic Offline Reinforcement Learning
  7. 2022Learning and Extrapolation of Robotic Skills using Task-Parameterized Equation Learner Networks
  8. 2026Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs