ENAP learns symbolic structures from visuomotor trajectories, outperforming SOTA methods by 27% in low-data regimes.

Yiyuan Pan, Xusheng Luo, Hanjiang Hu et al.

Proposes dynamic retargeting and control-guided RL for humanoid running at 3.3m/s, enabling autonomous, controllable, high-speed locomotion.

Zachary Olkin, William D. Compton, Ryan M. Bena et al.

ETA-VLA reduces computation by 32% via temporal fusion and sparsification, retaining 94% accuracy.

Yiru Wang, Anqing Jiang, Shuo Wang et al.

Chameleon enhances robotic manipulation with geometry-grounded multimodal memory, improving decision reliability in long-horizon tasks.

Xinying Guo, Chenxi Jiang, Hyun Bin Kim et al.

Proposes a PSTO-based decentralized end-to-end MARL framework enabling LiDAR-driven control for multi-UAV pursuit, achieving high success and scalability.

Yude Li, Zhexuan Zhou, Huizhe Li et al.

KG-M3PO integrates dynamic knowledge graphs into multi-task RL, achieving superior efficiency and generalization in partially observable robotic manipulation.

Aditya Narendra, Mukhammadrizo Maribjonov, Dmitry Makarov et al.

PRISM framework employs importance sampling and neural prediction to efficiently learn humanoid robot safe-stoppability boundaries, enabling proactive safety monitoring.

Yifan Sun, Yiyuan Pan, Shangtao Li et al.

DexDrummer combines trajectory planning and residual RL, achieving an F1 score of 1.0.

Hung-Chieh Fang, Amber Xie, Jennifer Grannen et al.

NMR framework addresses humanoid motion retargeting via dynamic mapping, significantly reducing joint jumps and self-collisions.

Qingrui Zhao, Kaiyue Yang, Xiyu Wang et al.

Vision pathways dominate action generation in VLA models; language sensitivity is task-dependent.

Bryce Grant, Xijia Zhao, Peng Wang

NavTrust benchmarks embodied navigation robustness by systematically introducing RGB, depth, and instruction corruptions, revealing significant robustness gaps in current models.

Huaide Jiang, Yash Chaudhary, Yuping Wang et al.

OmniVTA integrates predictive contact modeling with high-frequency tactile feedback for breakthroughs in contact-rich manipulation.

Yuhang Zheng, Songen Gu, Weize Li et al.

FASTER introduces Horizon-Aware Schedule to significantly reduce reaction latency in VLA models.

Yuxiang Lu, Zhe Liu, Xianzhe Fan et al.

Sparse Autoencoders reveal interpretable and steerable features in VLA models, enhancing generalization on the LIBERO benchmark.

Aiden Swann, Lachlain McGranahan, Hugo Buurmeijer et al.

ADMM-based distributed MPC with control barrier functions for quadrupedal robots reduces planning time by 51%.

Yicheng Zeng, Ruturaj S. Sambhus, Basit Muhammad Imran et al.

MAPG uses multi-agent probabilistic grounding for metric-semantic goal localization in vision-language navigation, excelling on the HM-EQA benchmark.

Swagat Padhan, Lakshya Jain, Bhavya Minesh Shah et al.

DriveVLM-RL uses dual-path VLM rewards in CARLA, cutting collision severity to 1.75 km/h.

Zilin Huang, Zihao Sheng, Zhengyang Wan et al.

AgentVLN employs VLM-as-Brain with cross-space mapping and active exploration, achieving superior long-horizon navigation with 73.5% success rate on RxR-CE.

Zihao Xin, Wentong Li, Yixuan Jiang et al.

Proposed a pipeline combining foundation models and MORL for context-aware human preference-driven robot navigation, enhancing adaptability and transparency.

Tharun Sethuraman, Subham Agrawal, Nils Dengler et al.

Introduces FloorPlan-VLN, leveraging structured floor plans as global priors, achieving over 60% success rate improvement with concise instructions.

Kehan Chen, Yan Huang, Dong An et al.