{"total":194,"rows":[{"id":"2410.24164","title":"$\\pi_0$: A Vision-Language-Action Flow Model for General Robot Control","created":"2024-10-31","cited_by_count":2407,"area":"vla"},{"id":"2504.16054","title":"$\\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization","created":"2025-04-22","cited_by_count":1761,"area":"vla"},{"id":"2501.09747","title":"FAST: Efficient Action Tokenization for Vision-Language-Action Models","created":"2025-01-16","cited_by_count":665,"area":"vla"},{"id":"2411.19650","title":"CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation","created":"2024-11-29","cited_by_count":422,"area":"vla"},{"id":"2510.13626","title":"LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models","created":"2025-10-15","cited_by_count":303,"area":"vla"},{"id":"2507.04447","title":"DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge","created":"2025-07-06","cited_by_count":213,"area":"vla"},{"id":"2503.10631","title":"HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model","created":"2025-03-13","cited_by_count":181,"area":"vla"},{"id":"2510.12276","title":"Spatial Forcing: Implicit Spatial Representation Alignment for Vision-language-action Model","created":"2025-10-14","cited_by_count":134,"area":"vla"},{"id":"2507.12440","title":"EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos","created":"2025-07-16","cited_by_count":128,"area":"vla"},{"id":"2502.14420","title":"ChatVLA: Unified Multimodal Understanding and Robot Control with Vision-Language-Action Model","created":"2025-02-20","cited_by_count":113,"area":"vla"},{"id":"2506.10100","title":"EfficientVLA: Training-Free Acceleration and Compression for Vision-Language-Action Models","created":"2025-06-11","cited_by_count":93,"area":"vla"},{"id":"2509.00576","title":"Galaxea Open-World Dataset and G0 Dual-System VLA Model","created":"2025-08-30","cited_by_count":92,"area":"vla"},{"id":"2503.02310","title":"PD-VLA: Accelerating Vision-Language-Action Model Integrated with Action Chunking via Parallel Decoding","created":"2025-03-04","cited_by_count":88,"area":"vla"},{"id":"2506.09937","title":"SAFE: Multitask Failure Detection for Vision-Language-Action Models","created":"2025-06-11","cited_by_count":80,"area":"vla"},{"id":"2411.13587","title":"Exploring the Adversarial Vulnerabilities of Vision-Language-Action Models in Robotics","created":"2024-11-18","cited_by_count":73,"area":"vla"},{"id":"2507.01016","title":"VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers","created":"2025-07-01","cited_by_count":70,"area":"vla"},{"id":"2510.21571","title":"Scalable Vision-Language-Action Model Pretraining for Robotic Manipulation with Real-Life Human Activity Videos","created":"2025-10-24","cited_by_count":70,"area":"vla"},{"id":"2508.13073","title":"Large VLM-based Vision-Language-Action Models for Robotic Manipulation: A Survey","created":"2025-08-18","cited_by_count":69,"area":"vla"},{"id":"2603.03596","title":"MEM: Multi-Scale Embodied Memory for Vision Language Action Models","created":"2026-03-04","cited_by_count":61,"area":"vla"},{"id":"2509.04996","title":"FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Action Flow Policies","created":"2025-09-05","cited_by_count":57,"area":"vla"},{"id":"2505.02152","title":"Interleave-VLA: Enhancing Robot Manipulation with Interleaved Image-Text Instructions","created":"2025-05-04","cited_by_count":51,"area":"vla"},{"id":"2508.19958","title":"Long-VLA: Unleashing Long-Horizon Capability of Vision Language Action Model for Robot Manipulation","created":"2025-08-27","cited_by_count":48,"area":"vla"},{"id":"2506.07530","title":"BitVLA: 1-bit Vision-Language-Action Models for Robotics Manipulation","created":"2025-06-09","cited_by_count":43,"area":"vla"},{"id":"2512.22414","title":"Emergence of Human to Robot Transfer in Vision-Language-Action Models","created":"2025-12-27","cited_by_count":42,"area":"vla"},{"id":"2511.04555","title":"Evo-1: Lightweight Vision-Language-Action Model with Preserved Semantic Alignment","created":"2025-11-06","cited_by_count":41,"area":"vla"},{"id":"2506.13725","title":"CEED-VLA: Consistency Vision-Language-Action Model with Early-Exit Decoding","created":"2025-06-16","cited_by_count":38,"area":"vla"},{"id":"2506.17561","title":"VLA-OS: Structuring and Dissecting Planning Representations and Paradigms in Vision-Language-Action Models","created":"2025-06-21","cited_by_count":36,"area":"vla"},{"id":"2509.12594","title":"The Better You Learn, The Smarter You Prune: Towards Efficient Vision-language-action Models via Differentiable Token Pruning","created":"2025-09-16","cited_by_count":36,"area":"vla"},{"id":"2503.13446","title":"MoManipVLA: Transferring Vision-language-action Models for General Mobile Manipulation","created":"2025-03-17","cited_by_count":34,"area":"vla"},{"id":"2510.24795","title":"A Survey on Efficient Vision-Language-Action Models","created":"2025-10-27","cited_by_count":34,"area":"vla"},{"id":"2512.11891","title":"VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer","created":"2025-12-09","cited_by_count":34,"area":"vla"},{"id":"2505.15660","title":"Exploring the Limits of Vision-Language-Action Manipulations in Cross-task Generalization","created":"2025-05-21","cited_by_count":33,"area":"vla"},{"id":"2412.20451","title":"CoA-VLA: Improving Vision-Language-Action Models via Visual-Textual Chain-of-Affordance","created":"2024-12-29","cited_by_count":31,"area":"vla"},{"id":"2602.20309","title":"QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models","created":"2026-02-23","cited_by_count":30,"area":"vla"},{"id":"2508.13446","title":"CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models","created":"2025-08-19","cited_by_count":29,"area":"vla"},{"id":"2602.03782","title":"QVLA: Not All Channels Are Equal in Vision-Language-Action Model's Quantization","created":"2026-02-03","cited_by_count":28,"area":"vla"},{"id":"2412.01034","title":"Quantization-Aware Imitation-Learning for Resource-Efficient Robotic Control","created":"2024-12-02","cited_by_count":25,"area":"vla"},{"id":"2511.18960","title":"AVA-VLA: Improving Vision-Language-Action models with Active Visual Attention","created":"2025-11-24","cited_by_count":25,"area":"vla"},{"id":"2506.17639","title":"RLRC: Reinforcement Learning-based Recovery for Compressed Vision-Language-Action Models","created":"2025-06-21","cited_by_count":23,"area":"vla"},{"id":"2507.05116","title":"VOTE: Vision-Language-Action Optimization with Trajectory Ensemble Voting","created":"2025-07-07","cited_by_count":22,"area":"vla"},{"id":"2512.14666","title":"EVOLVE-VLA: Test-Time Training from Environment Feedback for Vision-Language-Action Models","created":"2025-12-16","cited_by_count":22,"area":"vla"},{"id":"2602.01067","title":"A Systematic Study of Data Modalities and Strategies for Co-training Large Behavior Models for Robot Manipulation","created":"2026-02-01","cited_by_count":22,"area":"vla"},{"id":"2602.06556","title":"LIBERO-X: Robustness Litmus for Vision-Language-Action Models","created":"2026-02-06","cited_by_count":22,"area":"vla"},{"id":"2606.20092","title":"EventVLA: Event-Driven Visual Evidence Memory for Long-Horizon Vision-Language-Action Policies","created":"2026-06-18","cited_by_count":22,"area":"vla"},{"id":"2603.19199","title":"FASTER: Rethinking Real-Time Flow VLAs","created":"2026-03-19","cited_by_count":21,"area":"vla"},{"id":"2502.19250","title":"ObjectVLA: End-to-End Open-World Object Manipulation Without Demonstration","created":"2025-02-26","cited_by_count":20,"area":"vla"},{"id":"2509.02055","title":"Align-Then-stEer: Adapting the Vision-Language Action Models through Unified Latent Guidance","created":"2025-09-02","cited_by_count":20,"area":"vla"},{"id":"2511.16203","title":"When Alignment Fails: Multimodal Adversarial Attacks on Vision-Language-Action Models","created":"2025-11-20","cited_by_count":20,"area":"vla"},{"id":"2508.07650","title":"GraphCoT-VLA: A 3D Spatial-Aware Reasoning Vision-Language-Action Model for Robotic Manipulation with Ambiguous Instructions","created":"2025-08-11","cited_by_count":19,"area":"vla"},{"id":"2602.12978","title":"Learning Native Continuation for Action Chunking Flow Policies","created":"2026-02-13","cited_by_count":19,"area":"vla"},{"id":"2602.18397","title":"How Fast Can I Run My VLA? Demystifying VLA Inference Performance with VLA-Perf","created":"2026-02-20","cited_by_count":19,"area":"vla"},{"id":"2511.01571","title":"PixelVLA: Advancing Pixel-level Understanding in Vision-Language-Action Model","created":"2025-11-03","cited_by_count":18,"area":"vla"},{"id":"2512.21970","title":"StereoVLA: Enhancing Vision-Language-Action Models with Stereo Vision","created":"2025-12-26","cited_by_count":18,"area":"vla"},{"id":"2511.16449","title":"Bridging the Semantic-Action Gap in Visual Token Pruning for Efficient VLA Inference","created":"2025-11-20","cited_by_count":17,"area":"vla"},{"id":"2602.02142","title":"FD-VLA: Force-Distilled Vision-Language-Action Model for Contact-Rich Manipulation","created":"2026-02-02","cited_by_count":17,"area":"vla"},{"id":"2510.25889","title":"$\\pi_\\texttt{RL}$: Online RL Fine-tuning for Flow-based Vision-Language-Action Models","created":"2025-10-29","cited_by_count":16,"area":"vla"},{"id":"2605.14950","title":"Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model","created":"2026-05-14","cited_by_count":16,"area":"vla"},{"id":"2602.00557","title":"ConLA: Contrastive Latent Action Learning from Human Videos for Robotic Manipulation","created":"2026-01-31","cited_by_count":14,"area":"vla"},{"id":"2511.16175","title":"Mantis: A Versatile Vision-Language-Action Model with Disentangled Visual Foresight","created":"2025-11-20","cited_by_count":13,"area":"vla"},{"id":"2511.21192","title":"When Robots Obey the Patch: Universal Transferable Patch Attacks on Vision-Language-Action Models","created":"2025-11-26","cited_by_count":13,"area":"vla"},{"id":"2505.11214","title":"Unveiling the Potential of Vision-Language-Action Models with Open-Ended Multimodal Instructions","created":"2025-05-16","cited_by_count":12,"area":"vla"},{"id":"2505.15304","title":"Saliency-Aware Quantized Imitation Learning for Efficient Robotic Control","created":"2025-05-21","cited_by_count":12,"area":"vla"},{"id":"2511.12149","title":"AttackVLA: Benchmarking Adversarial and Backdoor Attacks on Vision-Language-Action Models","created":"2025-11-15","cited_by_count":12,"area":"vla"},{"id":"2603.07904","title":"DyQ-VLA: Temporal-Dynamic-Aware Quantization for Embodied Vision-Language-Action Models","created":"2026-03-09","cited_by_count":12,"area":"vla"},{"id":"2605.30877","title":"Wall-OSS-0.5 Technical Report","created":"2026-05-29","cited_by_count":12,"area":"vla"},{"id":"2511.21663","title":"Attention-Guided Patch-Wise Sparse Adversarial Attacks on Vision-Language-Action Models","created":"2025-11-26","cited_by_count":11,"area":"vla"},{"id":"2606.10267","title":"What Matters in Orchestrating Robot Policies: A Systematic Study of Hierarchical VLA Agents","created":"2026-06-09","cited_by_count":11,"area":"vla"},{"id":"2607.27205","title":"TurboVLA: Real-Time Vision-Language-Action Model at 32 Hz on an RTX 4090 with <1 GB VRAM","created":"2026-07-29","cited_by_count":10,"area":"vla"},{"id":"2505.11123","title":"Conditioning Matters: Training Diffusion Policies is Faster Than You Think","created":"2025-05-16","cited_by_count":9,"area":"vla"},{"id":"2509.08820","title":"RoboChemist: Long-Horizon and Safety-Compliant Robotic Chemical Experimentation","created":"2025-09-10","cited_by_count":9,"area":"vla"},{"id":"2510.18337","title":"MoTVLA: A Vision-Language-Action Model with Unified Fast-Slow Reasoning","created":"2025-10-21","cited_by_count":9,"area":"vla"},{"id":"2601.04266","title":"State Backdoor: Towards Stealthy Real-world Poisoning Attack on Vision-Language-Action Model in State Space","created":"2026-01-07","cited_by_count":9,"area":"vla"},{"id":"2602.22663","title":"Rethinking the Practicality of Vision-language-action Model: A Comprehensive Benchmark and An Improved Baseline","created":"2026-02-26","cited_by_count":9,"area":"vla"},{"id":"2603.01581","title":"KERV: Kinematic-Rectified Speculative Decoding for Embodied VLA Models","created":"2026-03-02","cited_by_count":9,"area":"vla"},{"id":"2603.25661","title":"Fast-dVLA: Accelerating Discrete Diffusion VLA to Real-Time Performance","created":"2026-03-26","cited_by_count":9,"area":"vla"},{"id":"2605.07308","title":"AT-VLA: Adaptive Tactile Injection for Enhanced Feedback Reaction in Vision-Language-Action Models","created":"2026-05-08","cited_by_count":9,"area":"vla"},{"id":"2505.03500","title":"VLAs are Confined yet Capable of Generalizing to Novel Instructions","created":"2025-05-06","cited_by_count":8,"area":"vla"},{"id":"2601.20262","title":"Shallow-{\\pi}: Knowledge Distillation for Flow-based VLAs","created":"2026-01-28","cited_by_count":8,"area":"vla"},{"id":"2602.21445","title":"VLA Knows Its Limits: Adaptive Execution Horizons for Robot Policies","created":"2026-02-24","cited_by_count":8,"area":"vla"},{"id":"2603.01549","title":"Pri4R: Learning World Dynamics for Vision-Language-Action Models with Privileged 4D Representation","created":"2026-03-02","cited_by_count":8,"area":"vla"},{"id":"2605.13778","title":"Realtime-VLA FLASH: Speculative Inference Framework for Diffusion-based VLAs","created":"2026-05-13","cited_by_count":8,"area":"vla"},{"id":"2605.24011","title":"ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models","created":"2026-05-19","cited_by_count":8,"area":"vla"},{"id":"2505.18793","title":"Genie Centurion: Accelerating Scalable Real-World Robot Training with Human Rewind-and-Refine Guidance","created":"2025-05-24","cited_by_count":7,"area":"vla"},{"id":"2508.15201","title":"Survey of Vision-Language-Action Models for Embodied Manipulation","created":"2025-08-21","cited_by_count":7,"area":"vla"},{"id":"2510.04898","title":"HyperVLA: Efficient Inference in Vision-Language-Action Models via Hypernetworks","created":"2025-10-06","cited_by_count":7,"area":"vla"},{"id":"2511.06202","title":"ExpReS-VLA: Specializing Vision-Language-Action Models Through Experience Replay and Retrieval","created":"2025-11-09","cited_by_count":7,"area":"vla"},{"id":"2511.17199","title":"VLA-4D: Embedding 4D Awareness into Vision-Language-Action Models for SpatioTemporally Coherent Robotic Manipulation","created":"2025-11-21","cited_by_count":7,"area":"vla"},{"id":"2512.18007","title":"Robotic VLA Benefits from Joint Learning with Motion Image Diffusion","created":"2025-12-19","cited_by_count":7,"area":"vla"},{"id":"2602.03445","title":"CRL-VLA: Continual Vision-Language-Action Learning","created":"2026-02-03","cited_by_count":7,"area":"vla"},{"id":"2603.10158","title":"Cross-Hand Latent Representation for Vision-Language-Action Models","created":"2026-03-10","cited_by_count":7,"area":"vla"},{"id":"2604.24447","title":"Characterizing Vision-Language-Action Models across XPUs: Constraints and Acceleration for On-Robot Deployment","created":"2026-04-27","cited_by_count":7,"area":"vla"},{"id":"2605.10925","title":"PriorVLA: Prior-Preserving Adaptation for Vision-Language-Action Models","created":"2026-05-11","cited_by_count":7,"area":"vla"},{"id":"2505.05540","title":"Benchmarking Vision, Language, & Action Models in Procedurally Generated, Open Ended Action Environments","created":"2025-05-08","cited_by_count":6,"area":"vla"},{"id":"2509.23655","title":"Focusing on What Matters: Object-Agent-centric Tokenization for Vision Language Action models","created":"2025-09-28","cited_by_count":6,"area":"vla"},{"id":"2601.19634","title":"AC^2-VLA: Action-Context-Aware Adaptive Computation in Vision-Language-Action Models for Efficient Robotic Manipulation","created":"2026-01-27","cited_by_count":6,"area":"vla"},{"id":"2602.09023","title":"TwinRL: Digital Twin-Driven Reinforcement Learning for Real-World Robotic Manipulation","created":"2026-02-09","cited_by_count":6,"area":"vla"},{"id":"2603.17573","title":"HeiSD: Hybrid Speculative Decoding for Embodied Vision-Language-Action Models with Kinematic Awareness","created":"2026-03-18","cited_by_count":6,"area":"vla"},{"id":"2603.28565","title":"StreamingVLA: Streaming Vision-Language-Action Model with Action Flow Matching and Adaptive Early Observation","created":"2026-03-30","cited_by_count":6,"area":"vla"},{"id":"2604.20834","title":"PokeVLA: Empowering Pocket-Sized Vision-Language-Action Model with Comprehensive World Knowledge Guidance","created":"2026-04-22","cited_by_count":6,"area":"vla"},{"id":"2607.06678","title":"NativeMEM: Native Memory Compression for Long-Horizon Robotic Manipulation","created":"2026-07-07","cited_by_count":6,"area":"vla"}],"next_cursor":"100"}