Key papers

• SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning (2025)
  Haozhan Li et al.
  18.35
• Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones (2020)
  Brijen Thananjeyan, Ashwin Balakrishna, Suraj Nair, et al.
  16.61
• DM-VIO: Delayed Marginalization Visual-inertial Odometry (2022)
  Lukas von Stumberg, Daniel Cremers
  16.19
• Self-organizing Maps For Storage And Transfer Of Knowledge In Reinforcement Learning (2018)
  Thommen George Karimpanal, Roland Bouffanais
  13.50
• Dual Latent Memory in Vision-Language-Action Models for Robotic Manipulation (2026)
  Hongyu Qu et al.
  12.88
• Safety Augmented Value Estimation From Demonstrations (SAVED): Safe Deep Model-based RL For Sparse Cost Robotic Tasks (2019)
  Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, et al.
  12.81
• Visuomotor Mechanical Search: Learning To Retrieve Target Objects In Clutter (2020)
  Andrey Kurenkov, Joseph Taglic, Rohun Kulkarni, et al.
  11.19
• ABot-M0.5: Unified Mobility-and-Manipulation World Action Model (2026)
  Ronghan Chen et al.
  11.17
• Learning To Locomote: Understanding How Environment Design Matters For Deep Reinforcement Learning (2020)
  Daniele Reda, Tianxin Tao, Michiel van de Panne
  10.97
• Domain Arithmetic: One-Shot VLA Adaptation under Environmental Shifts (2026)
  Taewook Kang et al.
  10.93
• Deep Reinforcement Learning With A Stage Incentive Mechanism Of Dense Reward For Robotic Trajectory Planning (2020)
  Gang Peng, Jin Yang, Xinde Lia, et al.
  10.61
• Revisiting Visual-inertial Structure From Motion For Odometry And SLAM Initialization (2020)
  Georgios Evangelidis, Branislav Micusik
  10.07
• An Optimal Online Method Of Selecting Source Policies For Reinforcement Learning (2017)
  Siyuan Li, Chongjie Zhang
  9.76
• Divis: Domain Invariant Visual Servoing For Collision-free Goal Reaching (2019)
  Fereshteh Sadeghi
  9.76
• Long-VLA: Unleashing Long-Horizon Capability of Vision Language Action Model for Robot Manipulation (2025)
  Yiguo Fan et al.
  9.30
• Admissible Abstractions For Near-optimal Task And Motion Planning (2018)
  William Vega-Brown, Nicholas Roy
  9.23
• Rl_reach: Reproducible Reinforcement Learning Experiments For Robotic Reaching Tasks (2021)
  Pierre Aumjaud, David McAuliffe, Francisco Javier Rodríguez Lera, et al.
  9.18
• GWM: Towards Scalable Gaussian World Models for Robotic Manipulation (2025)
  Guanxing Lu et al.
  8.71
• Learning From Imperfect Demonstrations From Agents With Varying Dynamics (2021)
  Zhangjie Cao, Dorsa Sadigh
  8.60
• Episodic Self-imitation Learning With Hindsight (2020)
  Tianhong Dai, Hengyan Liu, Anil Anthony Bharath
  8.09
• Curriculum Goal Masking For Continuous Deep Reinforcement Learning (2018)
  Manfred Eppe, Sven Magg, Stefan Wermter
  7.81
• ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning (2026)
  Yandan Yang et al.
  7.54
• Reinforcement Learning Via Recurrent Convolutional Neural Networks (2017)
  Tanmay Shankar, Santosha K. Dwivedy, Prithwijit Guha
  7.16
• Neural Packing: From Visual Sensing To Reinforcement Learning (2023)
  Juzhan Xu, Minglun Gong, Hao Zhang, et al.
  6.77
• GP3: A 3D Geometry-Aware Policy with Multi-View Images for Robotic Manipulation (2025)
  Quanhao Qian et al.
  6.75
• One-Shot Dual-Arm Imitation Learning (2025)
  Yilong Wang and Edward Johns
  6.63
• Act2Goal: From World Model To General Goal-conditioned Policy (2025)
  Pengfei Zhou et al.
  6.44
• DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning (2025)
  Zhengrong Xue et al.
  6.12
• Learning Multi-Stage Pick-and-Place with a Legged Mobile Manipulator (2025)
  Haichao Zhang et al.
  5.93
• RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies (2026)
  Tianxing Chen et al.
  5.88
• A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards (2025)
  Shivansh Patel et al.
  5.84
• Relevance-guided Unsupervised Discovery Of Abilities With Quality-diversity Algorithms (2022)
  Luca Grillotti, Antoine Cully
  5.84
• Autonomous Assessment Of Demonstration Sufficiency Via Bayesian Inverse Reinforcement Learning (2022)
  Tu Trinh, Haoyu Chen, Daniel S. Brown
  5.84
• Humanoid Locomotion and Manipulation: Current Progress and Challenges in Control, Planning, and Learning (2025)
  Zhaoyuan Gu et al.
  5.79
• Wake up for Touch! Mask-isolated Tactile Alignment Learning in MLLMs (2026)
  Yoonhyung Park et al.
  5.49
• Privacy-Preserving Depth-Only Open-Vocabulary 3D Semantic Segmentation Via Uncertainty-Guided Test-Time Optimization (2026)
  Xuying Huang et al.
  5.49
• Towards Metric-Agnostic Trajectory Forecasting (2026)
  Markus Knoche et al.
  5.49
• FOUND-IT: Foundation-model-first Task-driven 3D Scene Graphs with Granularity on Demand (2026)
  Dominic Maggio et al.
  5.38
• Composing Dextrous Grasping and In-hand Manipulation via Scoring with a Reinforcement Learning Critic (2025)
  Lennart R\"ostel et al.
  5.35
• GR00T N1: An Open Foundation Model for Generalist Humanoid Robots (2025)
  NVIDIA: Johan Bjorck et al.
  5.24
• Gemini Robotics: Bringing AI into the Physical World (2025)
  Gemini Robotics Team et al.
  5.24
• GLIB: Efficient Exploration For Relational Model-based Reinforcement Learning Via Goal-literal Babbling (2020)
  Rohan Chitnis, Tom Silver, Joshua Tenenbaum, et al.
  5.24
• Model-free Motion Planning Of Autonomous Agents For Complex Tasks In Partially Observable Environments (2023)
  Junchao Li, Mingyu Cai, Zhen Kan, et al.
  5.24
• Action-quantized Offline Reinforcement Learning For Robotic Skill Learning (2023)
  Jianlan Luo, Perry Dong, Jeffrey Wu, et al.
  5.24
• Generative Visual Foresight Meets Task-Agnostic Pose Estimation in Robotic Table-Top Manipulation (2025)
  Chuye Zhang et al.
  5.15
• SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training (2025)
  Mingdong Wu et al.
  5.04
• Structured 4D Latent Predictive Model for Robot Planning (2026)
  Zhiyi Li et al.
  5.01
• GPU-Parallel Linearization Error Bounds for Real-Time Robust Optimal Control of Nonlinear and Neural Network Dynamics (2026)
  Jeffrey Fang et al.
  5.01
• Overthink-Triggered Slowdown Attacks on LVLM-Based Robotic Systems (2026)
  Qiang Han et al.
  5.01
• PhysMani: Physics-principled 3D World Model for Dynamic Object Manipulation (2026)
  Peng Yun et al.
  5.01
• Cross-Platform Control for Autonomous Surface Vehicles via Adaptive Reinforcement Learning (2026)
  Ruiheng Jiang et al.
  5.01
• Bridge-WA: Predicting Where and How the World Changes for Robotic Action (2026)
  Yongjie Bai et al.
  5.01
• The Moving Eye: Enhancing VLA Spatial Generalization via Hybrid Dynamic Data Collection (2026)
  Jincheng Tang et al.
  5.01
• HEFT: Heavy-Payload Full-size Humanoid Teleoperation with Privileged Motion Guidance and Windowed Payload Curriculum (2026)
  Chenxin Liu et al.
  5.01
• ACID: Action Consistency via Inverse Dynamics for Planning with World Models (2026)
  Gawon Seo et al.
  5.01
• WorldSample: Closed-loop Real-robot RL with World Modelling (2026)
  Yuquan Xue et al.
  5.01
• Learning Agile Intruder Interception using Differentiable Quadrotor Dynamics (2026)
  Michael Anoruo et al.
  5.01
• VT-WAM: Visual-Tactile World Action Model for Contact-Rich Manipulation (2026)
  Shuai Tian et al.
  5.01
• TouchWorld: A Predictive and Reactive Tactile Foundation Model for Dexterous Manipulation (2026)
  Jianyi Zhou et al.
  5.01
• Smooth Operator: A Real-Time Sampling-Based Algorithm for Kinematic Hand Retargeting (2026)
  Robert Jomar Malate et al.
  5.01