DriveLMM-o-1
Emerging3papers using it
2025first seen
The 'DriveLMM-o1' dataset/benchmark is used to evaluate the performance of Vision-Language Models (VLMs) in autonomous driving by providing a framework for assessing their reliability and grounding capabilities in safety-critical scenarios.
Papers using DriveLMM-o-1 (3)
- OmniDrive-R1: Reinforcement-driven Interleaved Multi-modal Chain-of-Thought for Trustworthy Vision-Language Autonomous DrivingAgentThink: A Unified Framework for Tool-Augmented Chain-of-Thought Reasoning in Vision-Language Models for Autonomous DrivingDriveLMM-o1: A Step-by-Step Reasoning Dataset and Large Multimodal Model
for Driving Scenario Understanding