Hybrid Reasoning Based on Large Language Models for Autonomous Car Driving
Large Language Models (LLMs) have garnered significant attention for their ability to
understand text and images, generate human-like text, and perform complex reasoning …
understand text and images, generate human-like text, and perform complex reasoning …
Towards robust multi-modal reasoning via model selection
The reasoning capabilities of LLM (Large Language Model) are widely acknowledged in
recent research, inspiring studies on tool learning and autonomous agents. LLM serves as …
recent research, inspiring studies on tool learning and autonomous agents. LLM serves as …
Large language models for autonomous driving: Real-world experiments
Autonomous driving systems are increasingly popular in today's technological landscape,
where vehicles with partial automation have already been widely available on the market …
where vehicles with partial automation have already been widely available on the market …
Drivellm: Charting the path toward full autonomous driving with large language models
Human drivers instinctively reason with commonsense knowledge to predict hazards in
unfamiliar scenarios and to understand the intentions of other road users. However, this …
unfamiliar scenarios and to understand the intentions of other road users. However, this …
Quantifying and Mitigating Unimodal Biases in Multimodal Large Language Models: A Causal Perspective
Recent advancements in Large Language Models (LLMs) have facilitated the development
of Multimodal LLMs (MLLMs). Despite their impressive capabilities, MLLMs often suffer from …
of Multimodal LLMs (MLLMs). Despite their impressive capabilities, MLLMs often suffer from …
ChatGPT is on the horizon: could a large language model be suitable for intelligent traffic safety research and applications?
ChatGPT embarks on a new era of artificial intelligence and will revolutionize the way we
approach intelligent traffic safety systems. This paper begins with a brief introduction about …
approach intelligent traffic safety systems. This paper begins with a brief introduction about …
NPHardEval4V: A Dynamic Reasoning Benchmark of Multimodal Large Language Models
Understanding the reasoning capabilities of Multimodal Large Language Models (MLLMs) is
an important area of research. In this study, we introduce a dynamic benchmark …
an important area of research. In this study, we introduce a dynamic benchmark …
Chef: A comprehensive evaluation framework for standardized assessment of multimodal large language models
Multimodal Large Language Models (MLLMs) have shown impressive abilities in interacting
with visual content with myriad potential downstream tasks. However, even though a list of …
with visual content with myriad potential downstream tasks. However, even though a list of …
LLM-based Operating Systems for Automated Vehicles: A New Perspective
The deployment of large language models (LLMs) brings challenges to intelligent systems
because its capability of integrating large-scale training data facilitates contextual reasoning …
because its capability of integrating large-scale training data facilitates contextual reasoning …
Lampilot: An open benchmark dataset for autonomous driving with language model programs
Autonomous driving (AD) has made significant strides in recent years. However existing
frameworks struggle to interpret and execute spontaneous user instructions such as" …
frameworks struggle to interpret and execute spontaneous user instructions such as" …