Robotics Research Hub

VLA

50 papers

Vision-Language-Action models for generalist robot control.

sim-to-real reinforcement-learning vision vla manipulation uav foundation-models imitation-learning learning-from-demonstration benchmark dexterous offline-rl planning control human-robot-interaction perception representation-learning hand-tracking world-models benchmarking evaluation safety navigation vision-language locomotion il llm-robotics

Papers

Sorted by year (newest first)
3DThinkVLA: Endowing Vision-Language-Action Models with Latent 3D Priors via 3D-Thinking-Guided Co-training

3DThinkVLA: Endowing Vision-Language-Action Models with Latent 3D Priors via 3D-Thinking-Guided Co-training

Jiaxin Shi, Xidong Zhang, Fucai Zhu et al. · arXiv preprint · Jun 2026

We propose a 3D-thinking-guided co-training framework that enables vision-language-action (VLA) models to perform 3D spatial reasoning implicitly during action prediction. Our core insight is that 3D geometry perception and 3D spatial reasoning are distinct capabilities that can be disentangled and ...

sim-to-real reinforcement-learning vision vla manipulation
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No code repo Jun 2026
AIR-VLA+: Decoupling Movement and Manipulation via Cascaded Dual-Action Decoders with Asymmetric MoE for Aerial Robots

AIR-VLA+: Decoupling Movement and Manipulation via Cascaded Dual-Action Decoders with Asymmetric MoE for Aerial Robots

Jianli Sun, Bin Tian, Qiyao Zhang et al. · arXiv preprint · Jun 2026

Aerial manipulation systems have long suffered from representation coupling in end-to-end control, as platform-level Unmanned Aerial Vehicle (UAV) movement and end-effector-level arm manipulation differ substantially in action scale, dynamics, and control objectives. In this paper, we propose AIR-VL...

uav vla manipulation
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No code repo Jun 2026
AXIS: A Growable Community-Driven Data Engine for Scalable Robot Manipulation

AXIS: A Growable Community-Driven Data Engine for Scalable Robot Manipulation

Mengfei Zhao, Dihong Huang, Yikai Tang et al. · arXiv preprint · Jul 2026

Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale because they rely on specialized hardware, centralized operators, or fixed task suites. We present AXIS, a growable community-driven data engine a...

manipulation vision vla learning-from-demonstration benchmark
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No code repo Jul 2026
Continuous Actions from Discrete Minds: Latent-Aligned Planning for End-to-End Autonomous Driving

Continuous Actions from Discrete Minds: Latent-Aligned Planning for End-to-End Autonomous Driving

Ruoyu Yao, Yusen Xie, Qingzhao Liu et al. · arXiv preprint · Sep 2026

Bridging the gap between the discrete reasoning of Vision-Language Models and the continuous, physics-constrained nature of autonomous driving remains a significant challenge. In this work, we introduce LaPla, a unified Vision-Language-Action (VLA) framework featuring latent-aligned planning to s...

vision vla planning benchmark
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No code repo Sep 2026
Decoding Task Progress from VLA Representations

Decoding Task Progress from VLA Representations

Atiksh Bhardwaj, Edward Weiyi Duan, Prithwish Dan et al. · arXiv preprint · Aug 2026

Vision-language-action models (VLAs) are moving rapidly towards deployment as general-purpose manipulation policies, but we currently lack basic tools for understanding what these models represent internally or for monitoring them at runtime. Leveraging ideas from mechanistic interpretability, we...

manipulation vision vla reinforcement-learning control
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No code repo Aug 2026
Development of a Humanoid Robot Prototype for Multimodal Human-Robot Interaction

Development of a Humanoid Robot Prototype for Multimodal Human-Robot Interaction

Thang Tran Viet, Thanh Nguyen Canh, Huy Uong Gia et al. · arXiv preprint · Sep 2026

Human-robot interaction (HRI) enables intuitive and intelligent collaboration between humans and robots in real-world environments. This paper introduces a humanoid robot prototype designed as a flexible testbed for developing and integrating artificial intelligence (AI) modules in HRI tasks. The...

manipulation vision vla reinforcement-learning control human-robot-interaction
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GitHub ★ — Sep 2026
DexVerse: A Modular Benchmark for Multi-Task, Multi-Embodiment Dexterous Manipulation

DexVerse: A Modular Benchmark for Multi-Task, Multi-Embodiment Dexterous Manipulation

Yunchao Yao, Zhuxiu Xu, Tianqi Zhang et al. · arXiv preprint · Jul 2026

Building general-purpose dexterous manipulation policies requires benchmarks that go beyond isolated tasks to systematically evaluate policies across diverse interaction modes, sensory conditions, and robot embodiments. However, existing benchmarks remain limited in task and data diversity, embod...

manipulation vision vla reinforcement-learning control learning-from-demonstration benchmark
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No code repo Jul 2026
DynaFLIP: Rethinking Robotics Perception via Tri-Modal-Dynamics Guided Representation

DynaFLIP: Rethinking Robotics Perception via Tri-Modal-Dynamics Guided Representation

Jusuk Lee, Seungjae Lee, Jonghun Shin et al. · arXiv preprint · May 2026

Robot manipulation critically depends on perception that preserves the action-relevant aspects of a scene. Yet most robot learning pipelines are built upon visual encoders pre-trained for static recog

foundation-models perception manipulation representation-learning vla
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No code repo Code updated: May 2026
DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation

Junfeng Li, Junjie He, Zhide Zhong et al. · arXiv preprint · Aug 2026

Vision-Language-Action (VLA) models have become a powerful paradigm for robot manipulation, but training a single generalist policy for heterogeneous robot embodiments remains an open problem. Existing methods have two main limitations. First, they underuse dynamics priors shared across diverse v...

manipulation vision vla reinforcement-learning control benchmark
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No code repo Aug 2026
Evidence-Gated Task and Motion Planning with Vision-Language Models

Evidence-Gated Task and Motion Planning with Vision-Language Models

Tsunehiko Tanaka, Matthew Stephenson, Alistair Macvicar et al. · arXiv preprint · Aug 2026

Robots executing long-horizon manipulation tasks from natural-language instructions must reason about both semantic task structure and geometric feasibility. However, under partial observability, the availability of goal-relevant objects may be uncertain. In such cases, approaches that combine Vi...

manipulation vision vla reinforcement-learning planning
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No code repo Aug 2026
FabriVLA: A Lightweight Vision-Language-Action Model for Precise Multi-Task Manipulation

FabriVLA: A Lightweight Vision-Language-Action Model for Precise Multi-Task Manipulation

Shiyuan Yang, Borong Zhang, Jizheng Zhang et al. · arXiv preprint · Jul 2026

We present FabriVLA, a lightweight Vision-Language-Action model for Precise Multi-Task Manipulation. FabriVLA combines an InternVL3.5 vision-language backbone with a flow-matching action head featuring gated self-attention across action tokens and shallow VLM layer fusion for enriched spatial con...

manipulation vision vla reinforcement-learning benchmark
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No code repo Jul 2026
FARM: Reading Failure Signals from the Internal Predictive States of a Frozen Robotic World Model

FARM: Reading Failure Signals from the Internal Predictive States of a Frozen Robotic World Model

Haoran Pei, Mingrui Luo, Senbao Wang et al. · arXiv preprint · Sep 2026

Reliable robot deployment requires online failure monitoring, yet existing monitors mainly derive risk from proxy signals or train dedicated monitoring components. We ask whether the internal predictive states of a frozen pretrained robotic world model already contain directly decodable failure i...

vla reinforcement-learning benchmark
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No code repo Sep 2026
FlashVLA: Streaming Action Decoding for Fast and Asynchronous VLA Inference

FlashVLA: Streaming Action Decoding for Fast and Asynchronous VLA Inference

Zekai Li, Jiaming Tang, Zhijian Liu · arXiv preprint · Aug 2026

Vision-Language-Action (VLA) models are increasingly promising for robotic manipulation, yet their real-world deployment remains bottlenecked by high inference latency and unstable asynchronous execution. This challenge is particularly pronounced in flow-matching-based VLA models, where action de...

manipulation vision vla reinforcement-learning control
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GitHub ★ — Aug 2026
FolDeX: A Physical-World Benchmark for Long-Horizon Robotic Manipulation of Deformable Objects

FolDeX: A Physical-World Benchmark for Long-Horizon Robotic Manipulation of Deformable Objects

Chenhuan Liu, Yi Xu, Feng Wu et al. · arXiv preprint · Sep 2026

Embodied AI, including vision-language-action and world-action models, must operate reliably in the physical world. Yet methods that perform well in simulation can degrade substantially on real robots, especially in long-horizon deformable-object manipulation, where policies must track changing s...

manipulation vision vla reinforcement-learning control benchmark
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No code repo Sep 2026
GesVLA: Gesture-Aware Vision-Language-Action Model

GesVLA: Gesture-Aware Vision-Language-Action Model

Wenxuan Guo, Ziyuan Li, Meng Zhang et al. · arXiv preprint · May 2026

GesVLA augments standard VLA models with gesture awareness, enabling robots to interpret verbal instructions alongside human hand gestures for disambiguated manipulation.

vla manipulation hand-tracking
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GitHub ★ 18 Code updated: May 2026
GIFT: Guided Intermediate Feature Training via Action-Oriented Structural Supervision for Robotic Manipulation

GIFT: Guided Intermediate Feature Training via Action-Oriented Structural Supervision for Robotic Manipulation

Yupeng Zheng, Xiang Li, Songen Gu et al. · arXiv preprint · Sep 2026

Vision-language pre-training and predictive world modeling provide robot policies with rich semantic and dynamic visual features, but their native action and visual-prediction objectives may omit critical physical and task structure while retaining control-irrelevant visual redundancy. We call th...

manipulation vision vla reinforcement-learning control
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No code repo Sep 2026
HaWMPO: Hallucination-Aware World Model-based Policy Optimization for Generalist Robot Policy

HaWMPO: Hallucination-Aware World Model-based Policy Optimization for Generalist Robot Policy

Zengjue Chen, Peidong Liu, Jiawei Li et al. · arXiv preprint · Sep 2026

Generalist robot policies have demonstrated strong generalization across robotic manipulation tasks, yet their success rates remain limited in com- plex long-horizon scenarios. Recent methods improve Visual-Language-Action (VLA) policies through online reinforcement learning on real robots, but s...

manipulation vision vla reinforcement-learning benchmark
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No code repo Sep 2026
Improving Robotic Generalist Policies via Flow Reversal Steering

Improving Robotic Generalist Policies via Flow Reversal Steering

Andy Tang, William Chen, Andrew Wagenmaker et al. · arXiv preprint · Jun 2026

Generalist policies can learn a wide range of skills from diverse robot datasets. In order to solve or improve on challenging news tasks, we need a way to infer and invoke the appropriate actions from the policy's rich behavioral prior, especially when directly commanding the policy fails. We focus ...

manipulation vla world-models
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No code repo Jun 2026
LANTERN: A Closed-Loop Benchmark for VLM-Based Cooperative Driving with Temporally Grounded Warnings

LANTERN: A Closed-Loop Benchmark for VLM-Based Cooperative Driving with Temporally Grounded Warnings

Yongshuo Liu, Xu Gao, Morui Zhu et al. · arXiv preprint · Sep 2026

We present LANTERN, a closed-loop benchmark for temporally grounded cooperative warnings. LANTERN separates warning onset, hazard onset, warning termination, and post-hazard recovery, and evaluates each physical event under matched warning and no-warning executions so that the warning's contribut...

vision vla control benchmark
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No code repo Sep 2026
PhAIL: A Real-Robot VLA Benchmark and Distributional Methodology

PhAIL: A Real-Robot VLA Benchmark and Distributional Methodology

Sergey Arkhangelskiy · arXiv preprint · May 2026

Real-world evaluation of vision-language-action (VLA) policies still rests on binary success rate at a fixed timeout with N <= 25 rollouts per condition, almost always without confidence intervals or

benchmarking vla manipulation evaluation
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No code repo Code updated: May 2026
Planning-Oriented End-to-End Autonomous Driving: Architectures, Evaluation, and Emerging Paradigms

Planning-Oriented End-to-End Autonomous Driving: Architectures, Evaluation, and Emerging Paradigms

Yanchen Guan, Xingcheng Liu, Bin Rao et al. · arXiv preprint · Aug 2026

End-to-end autonomous driving has evolved from camera-to-control regression toward planning-oriented systems that use structured representations, trajectory-level outputs, and increasingly realistic evaluation protocols. This survey reviews this transition across behavior cloning, conditional imi...

vision vla reinforcement-learning planning control learning-from-demonstration benchmark
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No code repo Aug 2026
Reflex: Enabling Fast and Predictive Vision-Language-Action Models for Reaction-Critical Manipulation

Reflex: Enabling Fast and Predictive Vision-Language-Action Models for Reaction-Critical Manipulation

Yuxuan Chen, Wanruo Zhang, Xiao Li · arXiv preprint · Aug 2026

Vision-Language-Action (VLA) models have recently achieved promising performance in robotic manipulation. However, existing benchmarks mainly evaluate generalization on static manipulation tasks and largely overlook dynamic interaction scenarios. To address this gap, we present ReflexBench, a ben...

manipulation vision vla reinforcement-learning control benchmark
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GitHub ★ — Aug 2026
RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

Zhenxuan Fan, Bo Zhang, Yutong Lin et al. · arXiv preprint · Sep 2026

Vision-Language-Action (VLA) models have shown promising progress in language-conditioned robotic manipulation. However, existing datasets and benchmarks mainly evaluate task completion under predefined settings, offering limited insight into model reasoning under increasing spatial and procedura...

manipulation vision vla planning benchmark
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GitHub ★ — Sep 2026
RoboTTT: Context Scaling for Robot Policies

RoboTTT: Context Scaling for Robot Policies

Yunfan Jiang, Yevgen Chebotar, Ruijie Zheng et al. · arXiv preprint · Jul 2026

Recent robot foundation models operate with single-step or short-history visuomotor context. We introduce Test-Time-Training Robot Policies (RoboTTT), a robot model and training recipe that scale visuomotor context to 8K timesteps, three orders of magnitude beyond state-of-the-art policies, witho...

manipulation vision vla reinforcement-learning learning-from-demonstration
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GitHub ★ — Jul 2026
Same Trajectory, Contradictory Rewards (ROBORMBENCH): Paraphrase Fragility in Vision Language Reward Models

Same Trajectory, Contradictory Rewards (ROBORMBENCH): Paraphrase Fragility in Vision Language Reward Models

Wonje Jeung, Sangyeon Yoon, Hyesoo Hong et al. · arXiv preprint · Sep 2026

Vision-language models are increasingly used as reward functions for robotic learning, but this role requires paraphrase invariance: the same trajectory should receive the same reward under semantically equivalent goal descriptions. We show that current VLM reward models often violate this proper...

vision vla benchmark
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No code repo Sep 2026
STEP: State-Aware Task Estimation and Planning with Multi-Modal LLMs for Human-Robot Collaboration

STEP: State-Aware Task Estimation and Planning with Multi-Modal LLMs for Human-Robot Collaboration

Maitrey Gramopadhye, Prakash Baskaran, Xiao Liu et al. · arXiv preprint · Aug 2026

Effective human-robot collaboration in industrial settings requires robots to understand human intentions and assist with task planning, reducing workload. Recent works have explored the use of Multi-modal Large Language Models (MM-LLMs) for task planning in such data-scarce scenarios, leveraging...

vla planning
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No code repo Aug 2026
Stigmergic Graph Memory: An Environment-Aware Approach for Many-to-Many Multi-Agent Pickup and Delivery

Stigmergic Graph Memory: An Environment-Aware Approach for Many-to-Many Multi-Agent Pickup and Delivery

Aditya Dutta, Joon-Seok Kim · arXiv preprint · Jul 2026

Automated fulfillment warehouses must continuously assign and execute pickup-and-delivery work while avoiding congestion. In many-to-many Multi-Agent Pickup and Delivery (MAPD), a request specifies a stock-keeping unit rather than fixed endpoints, requiring the controller to select an agent, sour...

vla planning control
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No code repo Jul 2026
Towards Neuro-Symbolic Procedural Reasoning for Long-Horizon Vision-Language-Action Manipulation

Towards Neuro-Symbolic Procedural Reasoning for Long-Horizon Vision-Language-Action Manipulation

Vivek Chavan, Yahuan Shi, Oliver Heimann et al. · arXiv preprint · Sep 2026

Vision-language-action (VLA) models can execute short manipulation skills, but remain brittle in long-horizon procedures requiring persistent task state, dependency-aware reasoning, conditional decisions, and reliable grounding. We investigate a neuro-symbolic framework that combines learned VLA ...

manipulation vision vla reinforcement-learning control learning-from-demonstration
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No code repo Sep 2026
Uncertainty Quantification for Flow-Based Vision-Language-Action Models

Uncertainty Quantification for Flow-Based Vision-Language-Action Models

Ralf Römer, Maximilian Seeliger, Saida Liu et al. · RSS 2026 — Best Paper Award · Jun 2026

Quantifies epistemic uncertainty in flow-matching VLAs using velocity-field disagreement (VFD) across a small ensemble, enabling failure detection at deployment and sample-efficient active fine-tuning (SAVE).

vla foundation-models safety manipulation
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GitHub ★ — Jun 2026
UniMPA: A Unified Memory-Prediction-Action Model via Action-Grounded Transition Modeling

UniMPA: A Unified Memory-Prediction-Action Model via Action-Grounded Transition Modeling

Wei Li, Rui Shao, Jie He et al. · arXiv preprint · Sep 2026

Recent advances in Vision-Language-Action (VLA) models have improved robotic manipulation, yet observation-to-action learning remains limited by a fundamental transition realizability gap, manifested in three tightly coupled problems: (i) Transition ambiguity. Visually similar current observation...

manipulation vision vla reinforcement-learning
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GitHub ★ — Sep 2026
VLA-Corrector: Stage-Aware Observable State Understanding for Prompt-Based Closed-Loop Recovery of Vision-Language-Action Policies

VLA-Corrector: Stage-Aware Observable State Understanding for Prompt-Based Closed-Loop Recovery of Vision-Language-Action Policies

Chang Song, Bin Qian, Yan Feng et al. · arXiv preprint · Sep 2026

Long-horizon robot manipulation with Vision-Language-Action (VLA) policies remains vulnerable to execution-time deviations, as final task success provides little information for diagnosing and correcting failures caused by action noise, object displacement, or goal misalignment. We introduce a st...

manipulation vision vla reinforcement-learning benchmark
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No code repo Sep 2026
VoLN: Vision-Only Long-Horizon Navigation---Paradigm, Benchmark, and Method

VoLN: Vision-Only Long-Horizon Navigation---Paradigm, Benchmark, and Method

Jiabin Lou, Haopeng Wang, Yuanshuai Wang et al. · arXiv preprint · Jul 2026

Vision-and-Language Navigation (VLN) enables embodied agents to follow natural-language instructions. However, route-level instructions commonly encode spatial priors, such as orientation, distance, and layout, that are not explicitly available from onboard sensing at deployment in open, GPS-deni...

vision vla planning benchmark
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GitHub ★ — Jul 2026
What Matters, When? Diagnosing and Improving Conditional Visual Grounding in Visuomotor Imitation Policies

What Matters, When? Diagnosing and Improving Conditional Visual Grounding in Visuomotor Imitation Policies

Vivek Chavan, Pengtao Xie, Yahuan Shi et al. · arXiv preprint · Sep 2026

Visuomotor imitation policies can achieve high performance under in-distribution visual conditions yet fail when visually similar objects or receptacles are introduced. We study this behavior as a problem of conditional visual grounding: the visual target required for successful control changes w...

manipulation vision vla reinforcement-learning control
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No code repo Sep 2026
$ω$-0: A Latent Predictive World Action Model for Concurrent Humanoid Loco-Manipulation

$ω$-0: A Latent Predictive World Action Model for Concurrent Humanoid Loco-Manipulation

Zhe Li, Zhenzhe Zhang, Yangyang Wei et al. · arXiv preprint · Aug 2026

Humanoid household tasks often require concurrent loco-manipulation, where the robot must move, adjust posture, maintain balance, and manipulate objects as a single coordinated behavior. Yet existing humanoid policies typically decompose locomotion and manipulation, while recent world-action mode...

manipulation locomotion vision vla reinforcement-learning control learning-from-demonstration benchmark
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No code repo Aug 2026
GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

NVIDIA, :, Johan Bjorck et al. · arXiv preprint · Mar 2025

General-purpose robots need a versatile body and an intelligent mind. Recent advancements in humanoid robots have shown great promise as a hardware platform for building generalist autonomy in the human world. A robot foundation model, trained on massive and diverse data sources, is essential for...

manipulation vision vla reinforcement-learning control learning-from-demonstration benchmark
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GitHub ★ — Mar 2025
WholeBodyVLA: Towards Unified Latent VLA for Whole-Body Loco-Manipulation Control

WholeBodyVLA: Towards Unified Latent VLA for Whole-Body Loco-Manipulation Control

Haoran Jiang, Jin Chen, Qingwen Bu et al. · arXiv preprint · Dec 2025

Humanoid robots require precise locomotion and dexterous manipulation to perform challenging loco-manipulation tasks. Yet existing approaches, modular or end-to-end, are deficient in manipulation-aware locomotion. This confines the robot to a limited workspace, preventing it from performing large...

manipulation locomotion vision vla reinforcement-learning control learning-from-demonstration benchmark
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GitHub ★ — Dec 2025
π0: A Vision-Language-Action Flow Model for General Robot Control

π0: A Vision-Language-Action Flow Model for General Robot Control

Karl Pertsch, Oliver Groth, Jonas Frey et al. · arXiv preprint · Oct 2024

π0 is a 3.5B-parameter VLA flow model from Physical Intelligence that achieves state-of-the-art general robot manipulation by mixing online RL with high-quality human demonstrations, available as an open-source PyTorch implementation.

foundation-models vla manipulation il
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GitHub ★ 11,990 Code updated: May 2026
OpenVLA: An Open-Source Vision-Language-Action Model

OpenVLA: An Open-Source Vision-Language-Action Model

Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti et al. · arXiv · Jun 2024

A 7B-parameter open-source Vision-Language-Action model pre-trained on 970k real-world robot demonstrations, achieving strong generalization across robots and tasks.

vla llm-robotics foundation-models manipulation
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GitHub ★ 6,260 Code updated: May 2026
RT-1: Robotics Transformer for Real-World Control at Scale

RT-1: Robotics Transformer for Real-World Control at Scale

Anthony Brohan, Yevgen Chebotar, Chelsea Finn et al. · RSS 2023 · Jul 2023

RT-1 is a 35M-parameter transformer trained on 130K robot demonstrations that generalizes to new tasks, objects, and environments, forming the foundation for Google's RT-2 and RT-X line of VLA models.

foundation-models vla il manipulation
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GitHub ★ 1,723 Code updated: May 2026
FAST-LIO2: Fast Direct LiDAR-Inertial Odometry

FAST-LIO2: Fast Direct LiDAR-Inertial Odometry

Wei Xu, Yixi Cai, Dongjiao He et al. · IEEE T-RO · 2022

A tightly-coupled LiDAR-inertial odometry system with incremental kd-tree mapping, enabling real-time state estimation for UAVs and mobile robots.

uav vla foundation-models
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GitHub ★ 4,707 Code updated: May 2026

Suggested Learning Path

Read these papers in order to build expertise in VLA.

  1. 1
    3DThinkVLA: Endowing Vision-Language-Action Models with Latent 3D Priors via 3D-Thinking-Guided Co-training

    Jiaxin Shi, Xidong Zhang et al. · 2026

  2. 2
    AIR-VLA+: Decoupling Movement and Manipulation via Cascaded Dual-Action Decoders with Asymmetric MoE for Aerial Robots

    Jianli Sun, Bin Tian et al. · 2026

  3. 3
    ALAM: Algebraically Consistent Latent Transitions for Vision-Language-Action Models

    Zuojin Tang, Haoyun Liu et al. · 2026

  4. 4
    AwareVLN: Reasoning with Self-awareness for Vision-Language Navigation

    Wenxuan Guo, Xiuwei Xu et al. · 2026

  5. 5
    AXIS: A Growable Community-Driven Data Engine for Scalable Robot Manipulation

    Mengfei Zhao, Dihong Huang et al. · 2026

  6. 6
    BORA: Bridging Offline Reinforcement Learning and Online Residual Adaptation for Real-World Dexterous VLA Models

    Zhongxi Chen, Yifan Han et al. · 2026

…and 44 more papers.