{"total":103,"rows":[{"id":"2412.13877","title":"RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation","created":"2024-12-18","cited_by_count":175,"area":"offlinerl"},{"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":"2510.07077","title":"Vision-Language-Action Models for Robotics: A Review Towards Real-World Applications","created":"2025-10-08","cited_by_count":84,"area":"mllm"},{"id":"2501.07888","title":"Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video Understanding","created":"2025-01-14","cited_by_count":81,"area":"mllm"},{"id":"2506.24044","title":"A Survey on Vision-Language-Action Models for Autonomous Driving","created":"2025-06-30","cited_by_count":72,"area":"mllm"},{"id":"2503.20384","title":"MoLe-VLA: Dynamic Layer-skipping Vision Language Action Model via Mixture-of-Layers for Efficient Robot Manipulation","created":"2025-03-26","cited_by_count":70,"area":"mllm"},{"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":"2505.19017","title":"WorldEval: World Model as Real-World Robot Policies Evaluator","created":"2025-05-25","cited_by_count":68,"area":"wm"},{"id":"2505.21906","title":"ChatVLA-2: Vision-Language-Action Model with Open-World Embodied Reasoning from Pretrained Knowledge","created":"2025-05-28","cited_by_count":49,"area":"lr"},{"id":"2509.19012","title":"Pure Vision Language Action (VLA) Models: A Comprehensive Survey","created":"2025-09-23","cited_by_count":49,"area":"mllm"},{"id":"2502.14795","title":"Humanoid-VLA: Towards Universal Humanoid Control with Visual Integration","created":"2025-02-20","cited_by_count":45,"area":null},{"id":"2408.01129","title":"A Survey of Mamba","created":"2024-08-02","cited_by_count":39,"area":"ssm"},{"id":"2505.16640","title":"BadVLA: Towards Backdoor Attacks on Vision-Language-Action Models via Objective-Decoupled Optimization","created":"2025-05-22","cited_by_count":38,"area":"vla"},{"id":"2509.02722","title":"Planning with Reasoning using Vision Language World Model","created":"2025-09-02","cited_by_count":36,"area":"wm"},{"id":"2510.24795","title":"A Survey on Efficient Vision-Language-Action Models","created":"2025-10-27","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":"2507.22424","title":"Spec-VLA: Speculative Decoding for Vision-Language-Action Models with Relaxed Acceptance","created":"2025-07-30","cited_by_count":32,"area":"mllm"},{"id":"2505.21200","title":"Think Twice, Act Once: Token-Aware Compression and Action Reuse for Efficient Inference in Vision-Language-Action Models","created":"2025-05-27","cited_by_count":30,"area":"vla"},{"id":"2505.23450","title":"Agentic Robot: A Brain-Inspired Framework for Vision-Language-Action Models in Embodied Agents","created":"2025-05-29","cited_by_count":30,"area":"vla"},{"id":"2505.16517","title":"ManipLVM-R1: Reinforcement Learning for Reasoning in Embodied Manipulation with Large Vision-Language Models","created":"2025-05-22","cited_by_count":27,"area":"lr"},{"id":"2510.07181","title":"TIGeR: Tool-Integrated Geometric Reasoning in Vision-Language Models for Robotics","created":"2025-10-08","cited_by_count":27,"area":"lr"},{"id":"2511.10518","title":"SemanticVLA: Semantic-Aligned Sparsification and Enhancement for Efficient Robotic Manipulation","created":"2025-11-13","cited_by_count":21,"area":"vla"},{"id":"2603.19199","title":"FASTER: Rethinking Real-Time Flow VLAs","created":"2026-03-19","cited_by_count":21,"area":"vla"},{"id":"2506.09990","title":"Chain-of-Action: Trajectory Autoregressive Modeling for Robotic Manipulation","created":"2025-06-11","cited_by_count":17,"area":null},{"id":"2506.20966","title":"Parallels Between VLA Model Post-Training and Human Motor Learning: Progress, Challenges, and Trends","created":"2025-06-26","cited_by_count":17,"area":"mllm"},{"id":"2503.01616","title":"RoboDexVLM: Visual Language Model-Enabled Task Planning and Motion Control for Dexterous Robot Manipulation","created":"2025-03-03","cited_by_count":15,"area":"mllm"},{"id":"2601.06748","title":"On-the-Fly VLA Adaptation via Test-Time Reinforcement Learning","created":"2026-01-11","cited_by_count":14,"area":"vla"},{"id":"2506.18897","title":"MinD: Learning A Dual-System World Model for Real-Time Planning and Implicit Risk Analysis","created":"2025-06-23","cited_by_count":13,"area":"wm"},{"id":"2506.10826","title":"RationalVLA: A Rational Vision-Language-Action Model with Dual System","created":"2025-06-12","cited_by_count":12,"area":"vla"},{"id":"2509.15733","title":"GP3: A 3D Geometry-Aware Policy with Multi-View Images for Robotic Manipulation","created":"2025-09-19","cited_by_count":12,"area":null},{"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":"2509.08820","title":"RoboChemist: Long-Horizon and Safety-Compliant Robotic Chemical Experimentation","created":"2025-09-10","cited_by_count":9,"area":"vla"},{"id":"2603.23202","title":"Gaze-Regularized Vision-Language-Action Models for Robotic Manipulation","created":"2026-03-24","cited_by_count":9,"area":"vla"},{"id":"2602.16412","title":"ReMoRa: Multimodal Large Language Model based on Refined Motion Representation for Long-Video Understanding","created":"2026-02-18","cited_by_count":8,"area":"mllm"},{"id":"2603.12193","title":"SaPaVe: Towards Active Perception and Manipulation in Vision-Language-Action Models for Robotics","created":"2026-03-12","cited_by_count":8,"area":"vla"},{"id":"2409.02636","title":"Mamba as a motion encoder for robotic imitation learning","created":"2024-09-04","cited_by_count":7,"area":"ssm"},{"id":"2508.15201","title":"Survey of Vision-Language-Action Models for Embodied Manipulation","created":"2025-08-21","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":"2508.20840","title":"Learning Primitive Embodied World Models: Towards Scalable Robotic Learning","created":"2025-08-28","cited_by_count":6,"area":"wm"},{"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":"2510.07151","title":"ELMUR: External Layer Memory with Update/Rewrite for Long-Horizon RL Problems","created":"2025-10-08","cited_by_count":6,"area":null},{"id":"2512.20276","title":"ActionFlow: A Pipelined Action Acceleration for Vision Language Models on Edge","created":"2025-12-23","cited_by_count":6,"area":"mllm"},{"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":"2605.22671","title":"From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model","created":"2026-05-21","cited_by_count":6,"area":"vla"},{"id":"2511.18082","title":"ActDistill: General Action-Guided Self-Derived Distillation for Efficient Vision-Language-Action Models","created":"2025-11-22","cited_by_count":5,"area":"vla"},{"id":"2601.14945","title":"TIDAL: Temporally Interleaved Diffusion and Action Loop for High-Frequency VLA Control","created":"2026-01-21","cited_by_count":5,"area":"vla"},{"id":"2510.08044","title":"Towards Reliable LLM-based Robot Planning via Combined Uncertainty Estimation","created":"2025-10-09","cited_by_count":4,"area":"lr"},{"id":"2512.11362","title":"An Anatomy of Vision-Language-Action Models: From Modules to Milestones and Challenges","created":"2025-12-12","cited_by_count":4,"area":"vla"},{"id":"2512.19347","title":"OMP: One-step Meanflow Policy with Directional Alignment","created":"2025-12-22","cited_by_count":4,"area":"diffusion"},{"id":"2605.22283","title":"Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action","created":"2026-05-21","cited_by_count":4,"area":"vla"},{"id":"2411.17532","title":"FTMoMamba: Motion Generation with Frequency and Text State Space Models","created":"2024-11-26","cited_by_count":3,"area":"diffusion"},{"id":"2507.18276","title":"Adaptive Articulated Object Manipulation On The Fly with Foundation Model Reasoning and Part Grounding","created":"2025-07-24","cited_by_count":3,"area":null},{"id":"2510.06207","title":"EmbodiedCoder: Parameterized Embodied Mobile Manipulation via Modern Coding Model","created":"2025-10-07","cited_by_count":3,"area":"vla"},{"id":"2510.10160","title":"SaFiRe: Saccade-Fixation Reiteration with Mamba for Referring Image Segmentation","created":"2025-10-11","cited_by_count":3,"area":"ssm"},{"id":"2510.10181","title":"Dejavu: Towards Experience Feedback Learning for Embodied Intelligence","created":"2025-10-11","cited_by_count":3,"area":null},{"id":"2511.19528","title":"Discover, Learn, and Reinforce: Scaling Vision-Language-Action Pretraining with Diverse RL-Generated Trajectories","created":"2025-11-24","cited_by_count":3,"area":"vla"},{"id":"2602.21013","title":"Notes-to-Self: Scratchpad Augmented VLAs for Memory Dependent Manipulation Tasks","created":"2026-02-24","cited_by_count":3,"area":"vla"},{"id":"2606.13578","title":"LabVLA: Grounding Vision-Language-Action Models in Scientific Laboratories","created":"2026-06-11","cited_by_count":3,"area":"vla"},{"id":"2509.16900","title":"ME-Mamba: Multi-Expert Mamba with Efficient Knowledge Capture and Fusion for Multimodal Survival Analysis","created":"2025-09-21","cited_by_count":2,"area":"ssm"},{"id":"2510.24161","title":"BLM$_1$: A Boundless Large Model for Cross-Space, Cross-Task, and Cross-Embodiment Learning","created":"2025-10-28","cited_by_count":2,"area":"lr"},{"id":"2603.09542","title":"NS-VLA: Towards Neuro-Symbolic Vision-Language-Action Models","created":"2026-03-10","cited_by_count":2,"area":"vla"},{"id":"2603.15046","title":"AnoleVLA: Lightweight Vision-Language-Action Model with Deep State Space Models for Mobile Manipulation","created":"2026-03-16","cited_by_count":2,"area":"vla"},{"id":"2603.19131","title":"From Inference Efficiency to Embodied Efficiency: Revisiting Efficiency Metrics for Vision-Language-Action Models","created":"2026-03-19","cited_by_count":2,"area":"vla"},{"id":"2606.02775","title":"AURA: Action-Gated Memory for Robot Policies at Constant VRAM","created":"2026-06-01","cited_by_count":2,"area":"inference"},{"id":"2606.06556","title":"Robots Need More than VLA and World Models","created":"2026-06-04","cited_by_count":2,"area":"wm"},{"id":"2606.09630","title":"ReCoVLA: VLM-Guided Reward Compilation for Failure Recovery in Vision-Language-Action Policies","created":"2026-06-08","cited_by_count":2,"area":"vla"},{"id":"2606.31382","title":"Revisiting Parameter Redundancy in Vision-Language-Action Models: Insights from VLM-to-VLA Adaptation","created":"2026-06-30","cited_by_count":2,"area":"mllm"},{"id":"2607.10504","title":"SUREFlow: State-space Uncertainty-aware REsidual Flow Matching for Robust Robot Manipulation","created":"2026-07-11","cited_by_count":2,"area":"vla"},{"id":"2504.19683","title":"GPA-RAM: Grasp-Pretraining Augmented Robotic Attention Mamba for Spatial Task Learning","created":"2025-04-28","cited_by_count":1,"area":"ssm"},{"id":"2511.15279","title":"Look, Zoom, Understand: The Robotic Eyeball for Embodied Perception","created":"2025-11-19","cited_by_count":1,"area":null},{"id":"2512.02906","title":"MRD: Multi-resolution Retrieval-Detection Fusion for High-Resolution Image Understanding","created":"2025-12-02","cited_by_count":1,"area":"mllm"},{"id":"2601.17818","title":"ViTCoP: Accelerating Large Vision-Language Models via Visual and Textual Semantic Collaborative Pruning","created":"2026-01-25","cited_by_count":1,"area":"mllm"},{"id":"2602.00686","title":"Learning to Accelerate Vision-Language-Action Models through Adaptive Visual Token Caching","created":"2026-01-31","cited_by_count":1,"area":"vla"},{"id":"2602.16898","title":"MALLVI: A Multi-Agent Framework for Integrated Generalized Robotics Manipulation","created":"2026-02-18","cited_by_count":1,"area":"agents"},{"id":"2602.18813","title":"Habilis-$\\beta$: A Fast-Motion and Long-Lasting On-Device Vision-Language-Action Model","created":"2026-02-21","cited_by_count":1,"area":"vla"},{"id":"2603.00420","title":"TMR-VLA:Vision-Language-Action Model for Magnetic Motion Control of Tri-leg Silicone-based Soft Robot","created":"2026-02-28","cited_by_count":1,"area":null},{"id":"2605.25044","title":"X-DiffVLA: X-Embodied Diffusion Action Heads for Vision-Language-Action Models","created":"2026-05-24","cited_by_count":1,"area":"vla"},{"id":"2606.20246","title":"Finetuning Vision-Language-Action Models Requires Fewer Layers Than You Think","created":"2026-06-18","cited_by_count":1,"area":"vla"},{"id":"2608.10824","title":"Neural Introspection Gating for Adaptive KV-Cache Reuse in Vision-Language-Action Models","created":"2026-08-11","cited_by_count":1,"area":"vla"},{"id":"2608.24959","title":"GaussVLA: Geometry-Aware Spatial Reasoning for Vision-Language-Action Model","created":"2026-08-25","cited_by_count":1,"area":"lr"},{"id":"2608.29208","title":"AdaVLA: Adaptive Step Flow Matching for Training-free Acceleration of Vision-Language-Action Models","created":"2026-08-29","cited_by_count":1,"area":"lr"},{"id":"2609.05178","title":"LIBERO-RECOVER: Beyond Task Success Towards Failure Recovery in Robotic Manipulation Models","created":"2026-09-04","cited_by_count":1,"area":"vla"},{"id":"2609.07581","title":"ICI-VLA: In-Context Imitation with Spatiotemporally Aligned Demonstrations for Vision-Language-Action Models","created":"2026-09-07","cited_by_count":1,"area":"vla"},{"id":"2408.17081","title":"Stochastic Layer-Wise Shuffle for Improving Vision Mamba Training","created":"2024-08-30","cited_by_count":0,"area":"ssm"},{"id":"2505.18604","title":"Exemplar-Free Continual Learning for State Space Models","created":"2025-05-24","cited_by_count":0,"area":null},{"id":"2507.21589","title":"Exploring the Link Between Bayesian Inference and Embodied Intelligence: Toward Open Physical-World Embodied AI Systems","created":"2025-07-29","cited_by_count":0,"area":null},{"id":"2602.11919","title":"DynaHOI: Benchmarking Hand-Object Interaction for Dynamic Target","created":"2026-02-12","cited_by_count":0,"area":null},{"id":"2603.13587","title":"State-space models through the lens of ensemble control","created":"2026-03-13","cited_by_count":0,"area":null},{"id":"2604.08410","title":"BLaDA: Bridging Language to Functional Dexterous Actions within 3DGS Fields","created":"2026-04-09","cited_by_count":0,"area":null},{"id":"2605.05373","title":"Hidden States as Value Gradients: The Pontryagin Structure of Recurrent Policies","created":"2026-05-06","cited_by_count":0,"area":null},{"id":"2605.21854","title":"CrossVLA: Cross-Paradigm Post-Training and Inference Optimization for Vision-Language-Action Models","created":"2026-05-21","cited_by_count":0,"area":"vla"},{"id":"2606.10803","title":"Beyond APIs: Probing the Limits of MLLMs in Physical Tool Use","created":"2026-06-09","cited_by_count":0,"area":"mllm"},{"id":"2606.12910","title":"Bounding Boxes as Goals: Language-Conditioned Grasping via Neuro-Symbolic Planning","created":"2026-06-11","cited_by_count":0,"area":null},{"id":"2608.12932","title":"FlashDrive: Flash Vision-Language-Action Inference for Autonomous Driving","created":"2026-08-13","cited_by_count":0,"area":"vla"},{"id":"2608.13723","title":"Graph-MambaNav: Spatial-Temporal Graph Mamba Leveraging Object-Relation Knowledge for Object-Goal Navigation","created":"2026-08-13","cited_by_count":0,"area":"ssm"},{"id":"2608.15269","title":"Remember Smarter: Visual History Compressor and Hyperbolic Experience Space for Robotic Memory","created":"2026-08-15","cited_by_count":0,"area":"vla"},{"id":"2608.15509","title":"Temporal Logic Guided Universal Task Representations for Reinforcement Learning","created":"2026-08-16","cited_by_count":0,"area":"deeprl"},{"id":"2608.21407","title":"Mamba-based Selective State Space Modeling Improves the Accuracy-Complexity Tradeoff of SmolVLA Vision-Language-Action Experts","created":"2026-08-10","cited_by_count":0,"area":"vla"},{"id":"2609.09213","title":"Geometry Conditioning in an Embodied SLM: Training Controls and Robustness Diagnostics in a 0.8B Hybrid Model","created":"2026-09-06","cited_by_count":0,"area":null},{"id":"2609.19104","title":"rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference","created":"2026-09-16","cited_by_count":0,"area":"vla"}],"next_cursor":"100"}