# LeRobot: An Open-Source Library for End-to-End Robot Learning

arXiv: https://arxiv.org/abs/2602.22818 · HTML: https://mlsanity.com/paper/2602.22818/

## Key facts

- Cited by 73 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Feb 2026.

## Built on by (most cited first, 30 of 73)

- [FASTER: Rethinking Real-Time Flow VLAs](https://mlsanity.com/paper/2603.19199/) (2026)
- [stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation](https://mlsanity.com/paper/2605.21800/) (2026)
- [FutureRTC: Real-Time Robot Execution with Anticipatory-Conditioned Action Chunking](https://mlsanity.com/paper/2607.24008/) (2026)
- [MiraBench: Evaluating Action-Conditioned Reliability in Robotic World Models](https://mlsanity.com/paper/2605.29360/) (2026)
- [Open-AoE: An Open Egocentric Manipulation Dataset and Toolchain for Embodied Learning](https://mlsanity.com/paper/2607.14183/) (2026)
- [AR-VLA: True Autoregressive Action Expert for Vision-Language-Action Models](https://mlsanity.com/paper/2603.10126/) (2026)
- [Can Vision-Language-Action Models Learn from Real-World Data Continually without Forgetting?](https://mlsanity.com/paper/2605.26820/) (2026)
- [Spatially Aware World Action Model via Geometric Latent Diffusion](https://mlsanity.com/paper/2609.02531/) (2026)
- [Sword: Style-Robust World Models as Simulators via Dynamic Latent Bootstrapping for VLA Policy Post-Training](https://mlsanity.com/paper/2605.07288/) (2026)
- [Uncertainty Quantification for Flow-Based Vision-Language-Action Models](https://mlsanity.com/paper/2606.18043/) (2026)
- [SAIL: Test-Time Scaling for In-Context Imitation Learning with VLM](https://mlsanity.com/paper/2603.08269/) (2026)
- [Pipette: An Embodied Simulation Platform, Benchmark, and Data-Efficient Augmentation Framework for Wet-Lab Robotics](https://mlsanity.com/paper/2606.12936/) (2026)
- [μ0: A Scalable 3D Interaction-Trace World Model](https://mlsanity.com/paper/2606.13769/) (2026)
- [MA-VLA: Multi-Arm Vision-Language-Action Model for Collaboration and Compositional Generalization](https://mlsanity.com/paper/2608.25864/) (2026)
- [FiberTune: Preserving Action-Fiber Visual Residuals in Vision-Language-Action Fine-Tuning](https://mlsanity.com/paper/2606.08653/) (2026)
- [CofactVLA: Deconfounding Vision-Language-Action Models via Counterfactual Intervention](https://mlsanity.com/paper/2608.04396/) (2026)
- [DREAM: Deployment-Time Demonstration Generation via Real-to-Sim for Scalable Policy Adaptation](https://mlsanity.com/paper/2608.29078/) (2026)
- [SIM1: Physics-Aligned Simulator as Zero-Shot Data Scaler in Deformable Worlds](https://mlsanity.com/paper/2604.08544/) (2026)
- [AnchorRefine: Synergy-Manipulation Based on Trajectory Anchor and Residual Refinement for Vision-Language-Action Models](https://mlsanity.com/paper/2604.17787/) (2026)
- [EggHand: A Multimodal Foundation Model for Egocentric Hand Pose Forecasting](https://mlsanity.com/paper/2605.07642/) (2026)
- [Geometry Guided Self-Consistency for Physical AI](https://mlsanity.com/paper/2605.08638/) (2026)
- [D-VLA: A High-Concurrency Distributed Asynchronous Reinforcement Learning Framework for Vision-Language-Action Models](https://mlsanity.com/paper/2605.13276/) (2026)
- [Mag-VLA: Vision-Language-Action Model for Bimanual Magnetically Actuated Microrobot Manipulation](https://mlsanity.com/paper/2605.28486/) (2026)
- [Auditing Demonstration Curation Metrics: Action-Only Scorers Fail on the Structural Defects That Degrade Imitation Policies](https://mlsanity.com/paper/2606.05588/) (2026)
- [Targeting World Models to Compromise Robot Learning Pipelines](https://mlsanity.com/paper/2606.09499/) (2026)
- [What Demonstration Curation Metrics Do to Your Policy](https://mlsanity.com/paper/2606.10229/) (2026)
- [WOLF-VLA: Whole-Body Humanoid Optimal Locomotion Framework for Vision-Language-Action Learning](https://mlsanity.com/paper/2606.25591/) (2026)
- [The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks](https://mlsanity.com/paper/2606.28529/) (2026)
- [PAC-ACT: Post-training Actor-Critic for Action Chunking Transformers](https://mlsanity.com/paper/2607.09590/) (2026)
- [Lights, Camera, Malfunction: When Illumination Robustness Leaves VLA Models Blind to Color](https://mlsanity.com/paper/2607.14698/) (2026)

## Abstract (arXiv)

Robotics is undergoing a significant transformation powered by advances in high-level control techniques based on machine learning, giving rise to the field of robot learning. Recent progress in robot learning has been accelerated by the increasing availability of affordable teleoperation systems, large-scale openly available datasets, and scalable learning-based methods. However, development in the field of robot learning is often slowed by fragmented, closed-source tools designed to only address specific sub-components within the robotics stack. In this paper, we present textttlerobot, an open-source library that integrates across the entire robot learning stack, from low-level middleware communication for motor controls to large-scale dataset collection, storage and streaming. The library is designed with a strong focus on real-world robotics, supporting accessible hardware platforms while remaining extensible to new embodiments. It also supports efficient implementations for various state-of-the-art robot learning algorithms from multiple prominent paradigms, as well as a generalized asynchronous inference stack. Unlike traditional pipelines which heavily rely on hand-crafted techniques, textttlerobot emphasizes scalable learning approaches that improve directly with more data and compute. Designed for accessibility, scalability, and openness, textttlerobot lowers the barrier to entry for researchers and practitioners to robotics while providing a platform for reproducible, state-of-the-art robot learning.