From bf96f237893176b644b327973f20f96de787a8cb Mon Sep 17 00:00:00 2001 From: Daocheng Fu <1014991393@qq.com> Date: Tue, 19 Mar 2024 17:52:22 +0800 Subject: [PATCH] Update index.html --- index.html | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/index.html b/index.html index 53d6132..12a5453 100644 --- a/index.html +++ b/index.html @@ -118,7 +118,7 @@

Abstract

- This paper introduces LimSim++, an extended version of LimSim designed for the application of Multimodal Large Language Models ((M)LLMs) in autonomous driving. Acknowledging the limitations of existing simulation platforms, LimSim++ addresses the need for a long-term closed-loop infrastructure supporting continuous learning and improved generalization in autonomous driving. The platform offers extended-duration, multi-scenario simulations, providing crucial information for (M)LLM-driven vehicles. Users can engage in prompt engineering, model evaluation, and framework enhancement, making LimSim++ a versatile tool for research and practice. The contributions include the introduction of an open-source testing platform, a baseline MMLM-driven framework, and validation through quantitative experiments across diverse scenarios. LimSim++ serves as a crucial resource for advancing the integration of (M)LLMs in the development of trustworthy autonomous driving systems. The open-source resources are available at: Github: LimSim/LimSim_plus. + This paper introduces LimSim++, an extended version of LimSim designed for the application of Multimodal Large Language Models ((M)LLMs) in autonomous driving. Acknowledging the limitations of existing simulation platforms, LimSim++ addresses the need for a long-term closed-loop infrastructure supporting continuous learning and improved generalization in autonomous driving. The platform offers extended-duration, multi-scenario simulations, providing crucial information for (M)LLM-driven vehicles. Users can engage in prompt engineering, model evaluation, and framework enhancement, making LimSim++ a versatile tool for research and practice. The contributions include the introduction of an open-source testing platform, a baseline MMLM-driven framework, and validation through quantitative experiments across diverse scenarios. LimSim++ serves as a crucial resource for advancing the integration of (M)LLMs in the development of trustworthy autonomous driving systems. The open-source resources are available at Github: LimSim/LimSim_plus.