A survey on multimodal large language models for autonomous driving
With the emergence of Large Language Models (LLMs) and Vision Foundation Models
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …
Drivegpt4: Interpretable end-to-end autonomous driving via large language model
In the past decade, autonomous driving has experienced rapid development in both
academia and industry. However, its limited interpretability remains a significant unsolved …
academia and industry. However, its limited interpretability remains a significant unsolved …
Drivelm: Driving with graph visual question answering
We study how vision-language models (VLMs) trained on web-scale data can be integrated
into end-to-end driving systems to boost generalization and enable interactivity with human …
into end-to-end driving systems to boost generalization and enable interactivity with human …
Sed: A simple encoder-decoder for open-vocabulary semantic segmentation
Open-vocabulary semantic segmentation strives to distinguish pixels into different semantic
groups from an open set of categories. Most existing methods explore utilizing pre-trained …
groups from an open set of categories. Most existing methods explore utilizing pre-trained …
Vision language models in autonomous driving and intelligent transportation systems
The applications of Vision-Language Models (VLMs) in the fields of Autonomous Driving
(AD) and Intelligent Transportation Systems (ITS) have attracted widespread attention due to …
(AD) and Intelligent Transportation Systems (ITS) have attracted widespread attention due to …
Drivevlm: The convergence of autonomous driving and large vision-language models
A primary hurdle of autonomous driving in urban environments is understanding complex
and long-tail scenarios, such as challenging road conditions and delicate human behaviors …
and long-tail scenarios, such as challenging road conditions and delicate human behaviors …
Holistic Autonomous Driving Understanding by Bird's-Eye-View Injected Multi-Modal Large Models
The rise of multimodal large language models (MLLMs) has spurred interest in language-
based driving tasks. However existing research typically focuses on limited tasks and often …
based driving tasks. However existing research typically focuses on limited tasks and often …
Dolphins: Multimodal language model for driving
The quest for fully autonomous vehicles (AVs) capable of navigating complex real-world
scenarios with human-like understanding and responsiveness. In this paper, we introduce …
scenarios with human-like understanding and responsiveness. In this paper, we introduce …
Human-centric autonomous systems with llms for user command reasoning
The evolution of autonomous driving has made remarkable advancements in recent years,
evolving into a tangible reality. However, a human-centric large-scale adoption hinges on …
evolving into a tangible reality. However, a human-centric large-scale adoption hinges on …
Towards knowledge-driven autonomous driving
This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …
investigation highlights the limitations of current autonomous driving systems, in particular …