# Driving VLMs and open-vocabulary detection

Area: [Multimodal LLMs / vision-language models](https://mlsanity.com/mllm/index.md). HTML: https://mlsanity.com/mllm/driving-vlms-and-open-vocabulary-detection/

## Key facts

- Driving VLMs and open-vocabulary detection: 390 papers on arXiv since 2021 (data through 14 Oct 2026).
- 92 of its 390 mapped papers (24%) cite “DriveLM: Driving with Graph Visual Question Answering” (2023, arXiv 2312.14150).
- 82 of its 390 mapped papers (21%) cite “DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models” (2024, arXiv 2402.12289).
- 13 new papers 17 Sep–14 Oct.

## Most cited here

- [DriveLM: Driving with Graph Visual Question Answering](https://mlsanity.com/paper/2312.14150/) (2023), cited by 92 papers here
- [DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models](https://mlsanity.com/paper/2402.12289/) (2024), cited by 82 papers here
- [DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model](https://mlsanity.com/paper/2310.01412/) (2023), cited by 81 papers here
- [DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving](https://mlsanity.com/paper/2312.09245/) (2023), cited by 40 papers here
- [LingoQA: Visual Question Answering for Autonomous Driving](https://mlsanity.com/paper/2312.14115/) (2023), cited by 36 papers here
- [Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving](https://mlsanity.com/paper/2312.03661/) (2023), cited by 32 papers here
- [Vision Language Models in Autonomous Driving: A Survey and Outlook](https://mlsanity.com/paper/2310.14414/) (2023), cited by 30 papers here
- [Dolphins: Multimodal Language Model for Driving](https://mlsanity.com/paper/2312.00438/) (2023), cited by 30 papers here
- [A Survey on Multimodal Large Language Models for Autonomous Driving](https://mlsanity.com/paper/2311.12320/) (2023), cited by 27 papers here
- [Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives](https://mlsanity.com/paper/2501.04003/) (2025), cited by 27 papers here

## New (17 Sep–14 Oct)

- [DriveWLA: Unifying Future Dynamics and Scene Semantics through World-Language-Action Modeling for Autonomous Driving](https://mlsanity.com/paper/2610.17903/) (2026-10-13)
- [Not All Uncertainty Matters: Simulation-in-the-Loop Fast-Slow Reasoning for Decision-Critical Autonomous Driving System](https://mlsanity.com/paper/2610.09520/) (2026-10-07)
- [Localized Conformal Safety Monitoring with Vision-Language Models for Autonomous Driving](https://mlsanity.com/paper/2610.02765/) (2026-10-02)
- [Towards Reliable Vision-Language Models for Autonomous Driving](https://mlsanity.com/paper/2610.01531/) (2026-10-01)
- [Front-to-Back: Benchmarking Vision-Language Models for Asymmetric Cross-View Vehicle Re-Identification](https://mlsanity.com/paper/2609.39492/) (2026-09-30)
- [DrivingBench: Can Vision-Language Models Drive a Toyota Corolla?](https://mlsanity.com/paper/2609.38948/) (2026-09-30)
- [Vision-Language-Action Autonomous Driving Agent with Language-based Memory](https://mlsanity.com/paper/2609.38641/) (2026-09-29)
- [Speed in the Blind Spot: An Interpretability Analysis of Dynamic Perception in VLMs for Autonomous Driving](https://mlsanity.com/paper/2609.37046/) (2026-09-29)
- [BD-HazardVLM: Probing Vision-Language Models for Latent Defensive-Driving Hazards in Bangladesh Road Scenes](https://mlsanity.com/paper/2610.20627/) (2026-09-28)
- [AnchorReasoning: A Visual Grounding and Causal Reasoning Dataset in Long-Tail Autonomous Driving Scenarios](https://mlsanity.com/paper/2609.28366/) (2026-09-23)
- [CoVLM-Bench: A Real-World Benchmark for Cooperative Driving Question Answering and Planning](https://mlsanity.com/paper/2609.35823/) (2026-09-22)
- [Towards Systematic Qualification of Vision-Language Models for Automotive Perception Systems](https://mlsanity.com/paper/2609.25945/) (2026-09-22)
- [VeriFuse: Bounded Vision-Language Arbitration and Reason-Guided Refinement for Cooperative 3D Perception](https://mlsanity.com/paper/2609.21323/) (2026-09-18)