7 papers
EmbodiSkill: Skill-Aware Reflection for Self-Evolving Embodied Agents
Ruofei Ju, Xinrui Wang, Xin Ding +12
Embodied agents can benefit from skills that guide object search, action execution, and state changes across diverse environments. Since embodied environments vary across layouts,…
StepAudio 2.5 Technical Report
Bin Lin, Bo Zhao, Boyong Wu +98
Unified audio-language modeling has emerged as a prominent trend in modern speech systems, promising to bring the reasoning capabilities of large language models to auditory tasks.…
AwareVLN: Reasoning with Self-awareness for Vision-Language Navigation
Wenxuan Guo, Xiuwei Xu, Yichen Liu +7
Vision-and-Language Navigation (VLN) requires an agent to ground language instructions to its own movement within a visual environment. While state-of-the-art methods leverage the…
Temporal Sampling Frequency Matters: A Capacity-Aware Study of End-to-End Driving Trajectory Prediction
Yumao Liu, Tao Liu, Xiangyu Li +2
End to end (E2E) autonomous driving trajectory prediction is often trained with camera frames sampled at the highest available temporal frequency, assuming that denser sampling imp…
LLM-MLFFN: Multi-Level Autonomous Driving Behavior Feature Fusion via Large Language Model
Xiangyu Li, Tianyi Wang, Xi Cheng +5
Accurate classification of autonomous vehicle (AV) driving behaviors is critical for safety validation, performance diagnosis, and traffic integration analysis. However, existing a…
RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learning
Hao Gao, Shaoyu Chen, Bo Jiang +11
Existing end-to-end autonomous driving (AD) algorithms typically follow the Imitation Learning (IL) paradigm, which faces challenges such as causal confusion and an open-loop gap.…