39 citations · 135 across the 22 of their papers we have counts for
11 papers · 1 filter
Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
Zhe Chen, Weiyun Wang, Yue Cao +39
We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series that builds upon InternVL 2.0, maintaining its core model architecture while introducing signif…
ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving
Tao Ma, Hongbin Zhou, Qiusheng Huang +7
Offboard perception aims to automatically generate high-quality 3D labels for autonomous driving (AD) scenes. Existing offboard methods focus on 3D object detection with closed-set…
DreamForge: Motion-Aware Autoregressive Video Generation for Multi-View Driving Scenes
Jianbiao Mei, Tao Hu, Xuemeng Yang +7
Recent advances in diffusion models have improved controllable streetscape generation and supported downstream perception and planning tasks. However, challenges remain in accurate…
DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving
Xuemeng Yang, Licheng Wen, Yukai Ma +11
This paper presented DriveArena, the first high-fidelity closed-loop simulation system designed for driving agents navigating in real scenarios. DriveArena features a flexible, mod…
OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text
Qingyun Li, Zhe Chen, Weiyun Wang +37
Image-text interleaved data, consisting of multiple images and texts arranged in a natural document format, aligns with the presentation paradigm of internet data and closely resem…
DocGenome: An Open Large-scale Scientific Document Benchmark for Training and Testing Multi-modal Large Language Models
Renqiu Xia, Song Mao, Xiangchao Yan +19
Scientific documents record research findings and valuable human knowledge, comprising a vast corpus of high-quality data. Leveraging multi-modality data extracted from these docum…
Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving
Jianbiao Mei, Yukai Ma, Xuemeng Yang +11
Autonomous driving has advanced significantly due to sensors, machine learning, and artificial intelligence improvements. However, prevailing methods struggle with intricate scenar…
Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond
Zheng Zhu, Xiaofeng Wang, Wangbo Zhao +15
General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual en…
OASim: an Open and Adaptive Simulator based on Neural Rendering for Autonomous Driving
Guohang Yan, Jiahao Pi, Jianfei Guo +14
With deep learning and computer vision technology development, autonomous driving provides new solutions to improve traffic safety and efficiency. The importance of building high-q…
ChartX & ChartVLM: A Versatile Benchmark and Foundation Model for Complicated Chart Reasoning
Renqiu Xia, Bo Zhang, Hancheng Ye +9
Recently, many versatile Multi-modal Large Language Models (MLLMs) have emerged continuously. However, their capacity to query information depicted in visual charts and engage in r…
LimSim++: A Closed-Loop Platform for Deploying Multimodal LLMs in Autonomous Driving
Daocheng Fu, Wenjie Lei, Licheng Wen +5
The emergence of Multimodal Large Language Models ((M)LLMs) has ushered in new avenues in artificial intelligence, particularly for autonomous driving by offering enhanced understa…