{"total":58,"rows":[{"id":"2512.04797","title":"SIMA 2: A Generalist Embodied Agent for Virtual Worlds","created":"2025-12-04","cited_by_count":31,"area":"agents"},{"id":"2603.12942","title":"ReMem-VLA: Empowering Vision-Language-Action Model with Memory via Dual-Level Recurrent Queries","created":"2026-03-13","cited_by_count":29,"area":"vla"},{"id":"2601.15197","title":"LangForce: Bayesian Decomposition of Vision Language Action Models via Latent Action Queries","created":"2026-01-21","cited_by_count":27,"area":"vla"},{"id":"2511.15704","title":"In-N-On: Scaling Egocentric Manipulation with in-the-wild and on-task Data","created":"2025-11-19","cited_by_count":26,"area":null},{"id":"2512.04952","title":"FASTer: Toward Efficient Autoregressive Vision Language Action Modeling via Neural Action Tokenization","created":"2025-12-04","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":"2602.12281","title":"Scaling Verification Can Be More Effective than Scaling Policy Learning for Vision-Language-Action Alignment","created":"2026-02-12","cited_by_count":21,"area":"vla"},{"id":"2511.18810","title":"MergeVLA: Cross-Skill Model Merging Toward a Generalist Vision-Language-Action Agent","created":"2025-11-24","cited_by_count":18,"area":"mllm"},{"id":"2602.10556","title":"LAP: Language-Action Pre-Training Enables Zero-shot Cross-Embodiment Transfer","created":"2026-02-11","cited_by_count":18,"area":"vla"},{"id":"2602.15397","title":"ActionCodec: What Makes for Good Action Tokenizers","created":"2026-02-17","cited_by_count":18,"area":"mllm"},{"id":"2602.10983","title":"Scaling World Model for Hierarchical Manipulation Policies","created":"2026-02-11","cited_by_count":16,"area":"wm"},{"id":"2601.14133","title":"TwinBrainVLA: Unleashing the Potential of Generalist VLMs for Embodied Tasks via Asymmetric Mixture-of-Transformers","created":"2026-01-20","cited_by_count":14,"area":"mllm"},{"id":"2601.07823","title":"Robotic Video World Models: A Survey of Applications, Research Challenges, Future Directions","created":"2026-01-12","cited_by_count":13,"area":"wm"},{"id":"2605.30117","title":"VLA-Trace: Diagnosing Vision-Language-Action Models through Representation and Behavior Tracing","created":"2026-05-28","cited_by_count":13,"area":"vla"},{"id":"2605.13119","title":"Towards Long-horizon Embodied Agents with Tool-Aligned Vision-Language-Action Models","created":"2026-05-13","cited_by_count":9,"area":"vla"},{"id":"2604.14125","title":"HiVLA: A Visual-Grounded-Centric Hierarchical Embodied Manipulation System","created":"2026-04-15","cited_by_count":8,"area":"lr"},{"id":"2511.19878","title":"MAPS: Preserving Vision-Language Representations via Module-Wise Proximity Scheduling for Better Vision-Language-Action Generalization","created":"2025-11-25","cited_by_count":7,"area":"mllm"},{"id":"2602.03445","title":"CRL-VLA: Continual Vision-Language-Action Learning","created":"2026-02-03","cited_by_count":7,"area":"vla"},{"id":"2511.06619","title":"How Do VLAs Effectively Inherit from VLMs?","created":"2025-11-10","cited_by_count":6,"area":"vla"},{"id":"2607.13429","title":"Generalizable VLA Finetuning via Representation Anchoring and Language-Action Alignment","created":"2026-07-15","cited_by_count":6,"area":"mllm"},{"id":"2601.16667","title":"ReViP: Mitigating False Completion in Vision-Language-Action Models with Vision-Proprioception Rebalance","created":"2026-01-23","cited_by_count":5,"area":"vla"},{"id":"2604.04502","title":"Veo-Act: Enhancing VLA Policies with Frontier Video Models","created":"2026-04-06","cited_by_count":5,"area":"vla"},{"id":"2607.11119","title":"VIA: Visual Interface Agent for Robot Control","created":"2026-07-13","cited_by_count":5,"area":"vla"},{"id":"2510.03895","title":"NoTVLA: Semantics-Preserving Robot Adaptation via Narrative Action Interfaces","created":"2025-10-04","cited_by_count":4,"area":"vla"},{"id":"2606.09337","title":"TORL-VLA: Tactile Guided Online Reinforcement Learning for Contact-Rich Manipulation","created":"2026-06-08","cited_by_count":4,"area":"vla"},{"id":"2607.03751","title":"Look Before You Leap: Distilling Tree Search into Action Evaluation for Frozen VLA Models","created":"2026-07-04","cited_by_count":4,"area":"vla"},{"id":"2608.11671","title":"StellaVLA: In-Context Structured Demonstration for Generalizable Vision-Language-Action Models","created":"2026-08-12","cited_by_count":4,"area":"vla"},{"id":"2602.05049","title":"VISTA: Enhancing Visual Conditioning via Track-Following Preference Optimization in Vision-Language-Action Models","created":"2026-02-04","cited_by_count":3,"area":"vla"},{"id":"2609.29389","title":"Robo-Harness K1: Harnessing Robot-Use Agents via Perception Augmentation","created":"2026-09-24","cited_by_count":3,"area":"mllm"},{"id":"2605.06175","title":"VLA-GSE: Boosting Parameter-Efficient Fine-Tuning in VLA with Generalized and Specialized Experts","created":"2026-05-07","cited_by_count":2,"area":"vla"},{"id":"2605.15298","title":"PhysBrain 1.0 Technical Report","created":"2026-05-14","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":"2609.29964","title":"World Action Agent: Harnessing VLMs for Robot Manipulation via World Action Rehearsal","created":"2026-09-24","cited_by_count":2,"area":"lr"},{"id":"2605.08879","title":"Preserving Foundational Capabilities in Flow-Matching VLAs through Conservative SFT","created":"2026-05-09","cited_by_count":1,"area":"vla"},{"id":"2605.22183","title":"Action with Visual Primitives","created":"2026-05-21","cited_by_count":1,"area":"vla"},{"id":"2606.02277","title":"RoboSemanticBench: Diagnosing Semantic Grounding in Action Prediction for VLA Models","created":"2026-06-01","cited_by_count":1,"area":"vla"},{"id":"2606.23641","title":"Flatness Preserves Instruction Following in Vision-Language-Action Models","created":"2026-06-22","cited_by_count":1,"area":"vla"},{"id":"2608.27406","title":"CLAP: Cross-Embodiment Video World Models are Zero-Shot Physical Simulators","created":"2026-08-27","cited_by_count":1,"area":"wm"},{"id":"2603.20659","title":"StageCraft: Execution Aware Mitigation of Distractor and Obstruction Failures in VLA Models","created":"2026-03-21","cited_by_count":0,"area":"vla"},{"id":"2604.16067","title":"AEGIS: Anchor-Enforced Gradient Isolation for Knowledge-Preserving Vision-Language-Action Fine-Tuning","created":"2026-04-17","cited_by_count":0,"area":"mllm"},{"id":"2606.20980","title":"Robusto-2: Benchmarking Humans & VLMs for Autonomous Driving in Lima & New York City","created":"2026-06-18","cited_by_count":0,"area":"driving"},{"id":"2607.06882","title":"GemNav: Discrete-Token Visual Robot Navigation using a Multimodal Large Language Model","created":"2026-07-08","cited_by_count":0,"area":"mllm"},{"id":"2607.08974","title":"CLAP: Direct VLM-to-VLA Adaptation via Language-Action Grounding","created":"2026-07-09","cited_by_count":0,"area":"vla"},{"id":"2607.10744","title":"Traj-VLN: Learning Pixel-Space Interaction via Autoregressive Trajectory Generation","created":"2026-07-12","cited_by_count":0,"area":"lr"},{"id":"2607.19399","title":"Leveraging Offline Supervision for Efficient and Generalizable Reinforcement Learning in Large-Scale Vision-Language-Action Models","created":"2026-07-06","cited_by_count":0,"area":"vla"},{"id":"2608.19490","title":"Fine-Tuning VLAs with Self-Demonstrated Generative Control for Multi-Task Manipulation","created":"2026-08-19","cited_by_count":0,"area":"vla"},{"id":"2609.02341","title":"Towards Zero-Shot Transfer Across Embodiments For Driving VLAs","created":"2026-09-02","cited_by_count":0,"area":"lr"},{"id":"2609.08224","title":"3DWay: Generalizing Robot Manipulation via 3D Consistent Waypoints","created":"2026-09-08","cited_by_count":0,"area":"mllm"},{"id":"2609.18487","title":"ActionPiece: Rethinking Action Tokenization for Autoregressive Vision-Language-Action Models","created":"2026-09-16","cited_by_count":0,"area":"vla"},{"id":"2609.23944","title":"Topology-Informed Visual Prompting For Vision Language Action Policies","created":"2026-09-20","cited_by_count":0,"area":"vla"},{"id":"2609.38616","title":"Correcting WHERE, Preserving HOW: Compositional Generalization for Vision-Language-Action Models via Referential Guidance","created":"2026-09-29","cited_by_count":0,"area":"vla"},{"id":"2609.38989","title":"Cue the Flow: Steering Flow-Matching Policies for Open-World Delivery Manipulation","created":"2026-09-30","cited_by_count":0,"area":"diffusion"},{"id":"2610.05025","title":"Triggering Generalist Reasoning via Predictive Uncertainty for Dual-System VLA","created":"2026-10-04","cited_by_count":0,"area":"vla"},{"id":"2610.06078","title":"Do VLAs Understand and Adapt to the Objects They Handle, or Simply Replay Learned Behaviors?","created":"2026-10-05","cited_by_count":0,"area":null},{"id":"2610.08726","title":"EgoLAP: Learning from Egocentric Human Data through Language-Action Reasoning","created":"2026-10-06","cited_by_count":0,"area":null},{"id":"2610.13578","title":"RARA: Robust Policy Fine-Tuning through Retrieval-Anchored Representation Alignment for Robotic Manipulation","created":"2026-10-09","cited_by_count":0,"area":"vla"},{"id":"2610.14039","title":"RAIN: Robotic Task Generalization with Region-Aware Interaction Networks","created":"2026-10-02","cited_by_count":0,"area":"mllm"},{"id":"2610.20598","title":"DynThinker: Unifying Static 3D and Dynamic 4D Spatial Reasoning","created":"2026-10-14","cited_by_count":0,"area":"lr"}],"next_cursor":null}