Retrieval-augmented policy enables zero-shot extension of vision-language-action models at test time, reducing costs by replacing fine-tuning with retrieval.

Jeongeun Park, Juhan Park, Taekyung Kim et al.

TraCS integrates neuro-symbolic reasoning with motion prediction, improving accuracy and interpretability in multi-modal ground mobility.

Simon Kohaut, Felix Divo, Julius Hahnewald et al.

MemoryVAM integrates episodic memory into video world models using Recap-Cue, boosting long-horizon robot manipulation success from 5% to 42.5%.

Yuxin Jiang, Chang Yu, Yunuo Chen et al.

Proposes MoE-RM-SRL, integrating reward machines, safe distance, and sparse gating experts, achieving safe and efficient highway autonomous driving.

Chufei Yan, Zhihao Cui, Yiyan Lv et al.

Proposes Elastic Queries Reinforcement Learning (EQRL) for self-aware resource scheduling in VLA models, reducing inference costs while maintaining success.

Ge Wang, Xinyu Tan, Xiang Li et al.

AlignADV combines DPO and behavioral fingerprints, cutting training steps by up to 40.6%.

Yuewen Mei, Tong Nie, Jie Sun et al.

Flow Reversal Steering (FRS) leverages reverse flow models to map coarse actions into high-quality behaviors, boosting zero-shot control and rapid learning in robotic policies.

Andy Tang, William Chen, Andrew Wagenmaker et al.

Proposed MCR-Bionic hand integrates anatomical structural priors with hydraulic artificial muscles, achieving dexterous manipulation via wrist-finger coupling and intrinsic muscle pathways.

Haosen Yang, Guowu Wei

Sparse2Act achieves cross-domain robot manipulation using action-aligned sparse 3D representations, with 86.9% success on LIBERO-10.

Yu Guo, Chang Yu, Siyu Ma et al.

This paper introduces DIRECT, a multimodal scene-aware routing framework that dynamically allocates test-time compute among embodied planners, reducing latency by up to 65% while maintaining or surpassing top performance.

Jadelynn Dao, Milan Ganai, Yasmina Abukhadra et al.

Proposes DAR-Net, a transformer-based framework with pixel-level scene supervision, achieving 73.33% accuracy in underwater diver activity recognition on the first UDA dataset.

Sadman Sakib Enan, Junaed Sattar

A Unity-based virtual sea trial framework with traceable command-actuation logging supports IMO/ITTC-standard maneuvering data collection for USV system identification.

Paria Rezayan

JOIN employs opposition-score and task-conditioned manipulability for autonomous heterogeneous bimanual collaboration, achieving 95% success in real-world tests.

Drake Moore, Matt Cheng, Xiang Zhi Tan et al.

This paper introduces a fully distributed multi-UGV exploration framework combining descriptor-based loop closure detection and loop-aware hierarchical planning, achieving AR@1 of 89.9% and reducing exploration time by 15%.

Zhiwei Li, Haiou Liu, Xijun Zhao et al.

This paper introduces a language-driven adaptive cost optimization framework for autonomous driving, leveraging GPT-4 to interpret natural language queries and adjust MPPI control parameters in real-time.

Diego Martinez-Baselga, Khaled Mustafa, Javier Alonso-Mora

VeriSpace employs dual-path 3D scene encoding and spatial reasoning to enhance action verification in VLA models, improving accuracy by 15% on benchmarks.

Guiyu Zhao, Longteng Guo, Junyou Zhu et al.

YUBI: Efficient data collection for bimanual manipulation, 8434 hours, improves operational efficiency.

Takehiko Ohkawa, Jumpei Arima, Yuki Noguchi et al.

MemoryVLA++ integrates memory and imagination for full temporal modeling, significantly improving robotic task success rates.

Hao Shi, Weiye Li, Bin Xie et al.

iMaC translates future robot actions into image controls, significantly improving spatial accuracy in video prediction and policy evaluation.

Zhenyu Wu, Xiuwei Xu, Yukun Zhou et al.

DARP introduces difference-aware retrieval policies, leveraging local neighborhood structures to improve imitation learning robustness, achieving 15-46% performance gains over standard behavior cloning.

Quinn Pfeifer, Ethan Pronovost, Paarth Shah et al.