52 citations · 52 across the 9 of their papers we have counts for
12 papers
Rethinking Video Storage for AI Training: Breaking Cross-Frame Dependencies for Efficient Random Access
Zetian Song, Qize Yu, Yue Chen +10
Large-scale AI training increasingly relies on massive video datasets with random temporal sampling patterns. However, existing video storage paradigms are optimized for sequential…
AUGUstus: Autonomous Driving VLA Model with Unified Generation and Understanding
Yuqi Ye, Caigao Jiang, Zhuonan Wang +12
Vision-language-action (VLA) models show strong potential for end-to-end autonomous driving by leveraging world knowledge and understanding to excel in long-tail scenarios. However…
GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives
Qize Yu, Lianrui Fan, Boyu Chen +23
Precise grounding matters. It specifies which object is the target and where that object is, even in clutter and for tiny objects, and it has to be fast enough for closed-loop cont…
Sometimes You Gotta Run Before You Can Walk: Run-then-Walk Scheduling Strategy for VLM Autonomous Driving
Yuqi Ye, Shangkun Sun, Junhong Lin +6
Recent VLM-based autonomous driving planners adopt GRPO-style reinforcement learning to optimize driving performance. However, existing GRPO recipes either optimize driving efficie…
FactorDrive: Adaptive Multi-Step Reasoning Driven by Planning-Critical Factors for End-to-End Autonomous Driving
Guolei Huang, Tengfei She, Yuxuan Lu +3
Vision-language models (VLMs) have advanced scene understanding and enabled explicit reasoning in end-to-end autonomous driving. However, existing methods insufficiently integrate…
VGOcc: Learning Visual-Geometric Gaussians for Vision-Centric 3D Driving Occupancy Prediction
Junhong Lin, Xianda Guo, Kangli Wang +4
Vision-only occupancy prediction requires recovering a semantic 3D occupancy field from calibrated surround-view images, where each view provides observations with ambiguous depth…
: Unified Chain of Perception-Prediction-Planning Thought via Reinforcement Fine-Tuning
Yuqi Ye, Zijian Zhang, Junhong Lin +3
Vision-language models (VLMs) are increasingly being adopted for end-to-end autonomous driving systems due to their exceptional performance in handling long-tail scenarios. However…
AnyPcc: Compressing Any Point Cloud with a Single Universal Model
Kangli Wang, Qianxi Yi, Yuqi Ye +2
Generalization remains a critical challenge in deep learning-based point cloud geometry compression. While existing methods perform well on standard benchmarks, their performance c…
Generalized Gaussian Entropy Model for Point Cloud Attribute Compression with Dynamic Likelihood Intervals
Changhao Peng, Yuqi Ye, Wei Gao
Gaussian and Laplacian entropy models are proved effective in learned point cloud attribute compression, as they assist in arithmetic coding of latents. However, we demonstrate thr…
STFTCodec: High-Fidelity Audio Compression through Time-Frequency Domain Representation
Tao Feng, Zhiyuan Zhao, Yifan Xie +4
We present STFTCodec, a novel spectral-based neural audio codec that efficiently compresses audio using Short-Time Fourier Transform (STFT). Unlike waveform-based approaches that r…
LLM-PCGC: Large Language Model-based Point Cloud Geometry Compression
Yuqi Ye, Wei Gao
The key to effective point cloud compression is to obtain a robust context model consistent with complex 3D data structures. Recently, the advancement of large language models (LLM…
A Survey on Multilingual Large Language Models: Corpora, Alignment, and Bias
Yuemei Xu, Ling Hu, Jiayi Zhao +4
Based on the foundation of Large Language Models (LLMs), Multilingual LLMs (MLLMs) have been developed to address the challenges faced in multilingual natural language processing,…