2 citations · 10 across the 18 of their papers we have counts for
22 papers
CALR: Continuous Anchored Latent Reasoning via Render-of-Thought Compression
Zhaoyang Wei, Bowen Jiang, Yanchao Hao +5
Visual latent reasoning compresses rendered derivations into compact intermediate states, reducing textual reasoning overhead. Existing approaches differ in how they represent thes…
Video-HolmesV2: Can MLLMs Reason with Spatio-Temporal Audio-Visual Evidence in Long Videos?
Zhaoyang Wei, Zipeng Wang, Yushe Cao +10
Multimodal Large Language Models have demonstrated impressive video understanding, yet their ability to reason over long-form narratives is often masked by visual-centric evaluatio…
AutoSpeed: Annotation-Free Stage-Adaptive Motion Speed Learning for Robot Manipulation
Qingda Hu, Ziheng Qiu, Jieru Zhao +2
Different stages of manipulation tasks exhibit varying levels of difficulty, suggesting stage-dependent motion speeds and temporal prediction horizons. However, existing IL-based v…
Learning A Unified Risk Map for Autonomous Driving in Partially Observable Environments
Jie Jia, Yaofeng Su, Zeyu Bao +4
Occlusion-aware prediction remains a critical challenge in autonomous driving due to the inherent uncertainty of unobserved regions. Existing approaches either overestimate risk ba…
Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving
Zhihua Hua, Junli Wang, Pengfei LI +6
Global navigation information and local scene understanding are two crucial components of autonomous driving systems. However, our experimental results indicate that many end-to-en…
Self-Evolutionary Replanning for Failure-Aware Motion Planning
Guoliang Li, Ruihua Han, Chengyang Li +5
Motion planners tuned under nominal conditions can fail when execution conditions change. Existing differentiable adaptation methods provide efficient online updates but remain con…
CMoE: Contrastive Mixture of Experts for Motion Control and Terrain Adaptation of Humanoid Robots
Shihao Ma, Hongjin Chen, Zijun Xu +6
For effective deployment in real-world environments, humanoid robots must autonomously navigate a diverse range of complex terrains with abrupt transitions. While the Vanilla mixtu…
Rhythm: Learning Interactive Whole-Body Control for Dual Humanoids
Hongjin Chen, Wei Zhang, Pengfei Li +10
Realizing interactive whole-body control for multi-humanoid systems is critical for unlocking complex collaborative capabilities in shared environments. Although recent advancement…
Drive in Corridors: Enhancing the Safety of End-to-end Autonomous Driving via Corridor Learning and Planning
Zhiwei Zhang, Ruichen Yang, Ke Wu +5
Safety remains one of the most critical challenges in autonomous driving systems. In recent years, the end-to-end driving has shown great promise in advancing vehicle autonomy in a…
Collaborative Learning of Local 3D Occupancy Prediction and Versatile Global Occupancy Mapping
Shanshuai Yuan, Julong Wei, Muer Tie +3
Vision-based 3D semantic occupancy prediction is vital for autonomous driving, enabling unified modeling of static infrastructure and dynamic agents. Global occupancy maps serve as…
Topology-Driven Trajectory Optimization for Modelling Controllable Interactions Within Multi-Vehicle Scenario
Changjia Ma, Yi Zhao, Zhongxue Gan +2
Trajectory optimization in multi-vehicle scenarios faces challenges due to its non-linear, non-convex properties and sensitivity to initial values, making interactions between vehi…
VINGS-Mono: Visual-Inertial Gaussian Splatting Monocular SLAM in Large Scenes
Ke Wu, Zicheng Zhang, Muer Tie +3
VINGS-Mono is a monocular (inertial) Gaussian Splatting (GS) SLAM framework designed for large scenes. The framework comprises four main components: VIO Front End, 2D Gaussian Map,…
Planning by Simulation: Motion Planning with Learning-based Parallel Scenario Prediction for Autonomous Driving
Tian Niu, Kaizhao Zhang, Zhongxue Gan +1
Planning safe trajectories for autonomous vehicles is essential for operational safety but remains extremely challenging due to the complex interactions among traffic participants.…
HGS-Planner: Hierarchical Planning Framework for Active Scene Reconstruction Using 3D Gaussian Splatting
Zijun Xu, Rui Jin, Ke Wu +6
In complex missions such as search and rescue,robots must make intelligent decisions in unknown environments, relying on their ability to perceive and understand their surroundings…
SparseTem: Boosting the Efficiency of CNN-Based Video Encoders by Exploiting Temporal Continuity
Kunyun Wang, Shuo Yang, Jieru Zhao +4
Deep learning models have become pivotal in the field of video processing and is increasingly critical in practical applications such as autonomous driving and object detection. Al…
Inf-MLLM: Efficient Streaming Inference of Multimodal Large Language Models on a Single GPU
Zhenyu Ning, Jieru Zhao, Qihao Jin +2
Multimodal Large Language Models (MLLMs) are distinguished by their multimodal comprehensive ability and widely used in many real-world applications including GPT-4o, autonomous dr…
OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving
Julong Wei, Shanshuai Yuan, Pengfei Li +3
The rise of multi-modal large language models(MLLMs) has spurred their applications in autonomous driving. Recent MLLM-based methods perform action by learning a direct mapping fro…
Learning Occlusion-aware Decision-making from Agent Interaction via Active Perception
Jie Jia, Yiming Shu, Zhongxue Gan +1
Occlusion-aware decision-making is essential in autonomous driving due to the high uncertainty of various occlusions. Recent occlusion-aware decision-making methods encounter issue…
AutoVCoder: A Systematic Framework for Automated Verilog Code Generation using LLMs
Mingzhe Gao, Jieru Zhao, Zhe Lin +5
Recently, the use of large language models (LLMs) for software code generation, e.g., C/C++ and Python, has proven a great success. However, LLMs still suffer from low syntactic an…
O2V-Mapping: Online Open-Vocabulary Mapping with Neural Implicit Representation
Muer Tie, Julong Wei, Zhengjun Wang +7
Online construction of open-ended language scenes is crucial for robotic applications, where open-vocabulary interactive scene understanding is required. Recently, neural implicit…
HGS-Mapping: Online Dense Mapping Using Hybrid Gaussian Representation in Urban Scenes
Ke Wu, Kaizhao Zhang, Zhiwei Zhang +7
Online dense mapping of urban scenes forms a fundamental cornerstone for scene understanding and navigation of autonomous vehicles. Recent advancements in mapping methods are mainl…
OpenAnnotate3D: Open-Vocabulary Auto-Labeling System for Multi-modal 3D Data
Yijie Zhou, Likun Cai, Xianhui Cheng +3
In the era of big data and large models, automatic annotating functions for multi-modal data are of great significance for real-world AI-driven applications, such as autonomous dri…