mlsanityData to 14 Oct 2026

ADS-Edit: A Multimodal Knowledge Editing Dataset for Autonomous Driving Systems

arXiv 2503.20756 ↗First posted 26 Mar 2025cs.CL cs.AI cs.CVcited by 0

On the map: Multimodal LLMs / vision-language models → Driving VLMs and open-vocabulary detection

Abstract (arXiv)

Recent advancements in Large Multimodal Models (LMMs) have shown promise in Autonomous Driving Systems (ADS). However, their direct application to ADS is hindered by challenges such as misunderstanding of traffic knowledge, complex road conditions, and diverse states of vehicle. To address these challenges, we propose the use of Knowledge Editing, which enables targeted modifications to a model's behavior without the need for full retraining. Meanwhile, we introduce ADS-Edit, a multimodal knowledge editing dataset specifically designed for ADS, which includes various real-world scenarios, multiple data types, and comprehensive evaluation metrics. We conduct comprehensive experiments and derive several interesting conclusions. We hope that our work will contribute to the further advancement of knowledge editing applications in the field of autonomous driving. Code and data are available in https://github.com/zjunlp/EasyEdit/blob/main/examples/ADSEdit.md.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Driving VLMs and open-vocabulary detection, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 50 of its 72 references that are in the map. First posted on arXiv 26 Mar 2025.

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50 of 72 references.

Closest ancestors · 5

Same direction, newest first

  1. 2024OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving19 Dec
  2. 2024Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases16 Apr
  3. 2023DriveLM: Driving with Graph Visual Question Answering21 Dec
  4. 2023LingoQA: Visual Question Answering for Autonomous Driving21 Dec
  5. 2023A Survey on Multimodal Large Language Models for Autonomous Driving21 Nov

Other references · 45

  1. 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,234
  2. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,418
  3. 2024LLaVA-OneVision: Easy Visual Task Transfercited by 2,719
  4. 2022Locating and Editing Factual Associations in GPTcited by 2,691
  5. 2015VQA: Visual Question Answeringcited by 2,506
  6. 2022Mass-Editing Memory in a Transformercited by 1,001
  7. 2024DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understandingcited by 572
  8. 2023Editing Large Language Models: Problems, Methods, and Opportunitiescited by 372
  9. 2023Can We Edit Factual Knowledge by In-Context Learning?cited by 285
  10. 2022Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptorscited by 271
  11. 2023NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenariocited by 262
  12. 2024AlphaEdit: Null-Space Constrained Knowledge Editing for Language Modelscited by 236
33 more
  1. 2024NVILA: Efficient Frontier Visual Language Modelscited by 209
  2. 2024Model Editing at Scale leads to Gradual and Catastrophic Forgettingcited by 93
  3. 2025AnyEdit: Edit Any Knowledge Encoded in Language Modelscited by 76
  4. 2024Learning to Edit: Aligning LLMs with Knowledge Editingcited by 43
  5. 2024Uncovering Overfitting in Large Language Model Editingcited by 39
  6. 2025Parameters vs. Context: Fine-Grained Control of Knowledge Reliance in Language Modelscited by 39
  7. 2024AKEW: Assessing Knowledge Editing in the Wildcited by 36
  8. 2024DeepEdit: Knowledge Editing as Decoding with Constraintscited by 33
  9. 2024VLKEB: A Large Vision-Language Model Knowledge Editing Benchmarkcited by 30
  10. 2025The Mirage of Model Editing: Revisiting Evaluation in the Wildcited by 27
  11. 2024MIKE: A New Benchmark for Fine-grained Multimodal Entity Knowledge Editingcited by 25
  12. 2024MC-MKE: A Fine-Grained Multimodal Knowledge Editing Benchmark Emphasizing Modality Consistencycited by 22
  13. 2024CodeUpdateArena: Benchmarking Knowledge Editing on API Updatescited by 19
  14. 2025Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuningcited by 19
  15. 2024Multilingual Knowledge Editing with Language-Agnostic Factual Neuronscited by 18
  16. 2024Towards Unified Multimodal Editing with Enhanced Knowledge Collaborationcited by 18
  17. 2025Precise Localization of Memories: A Fine-grained Neuron-level Knowledge Editing Technique for LLMscited by 18
  18. 2025Knowledge Updating? No More Model Editing! Just Selective Contextual Reasoningcited by 16
  19. 2025Position: Editing Large Language Models Poses Serious Safety Riskscited by 15
  20. 2024BMIKE-53: Investigating Cross-Lingual Knowledge Editing with In-Context Learningcited by 13
  21. 2024CALMM-Drive: Confidence-Aware Autonomous Driving with Large Multimodal Modelcited by 12
  22. 2024Editing Factual Knowledge and Explanatory Ability of Medical Large Language Modelscited by 10
  23. 2024MQA-KEAL: Multi-hop Question Answering under Knowledge Editing for Arabic Languagecited by 9
  24. 2025CaKE: Circuit-aware Editing Enables Generalizable Knowledge Learnerscited by 9
  25. 2024O-Edit: Orthogonal Subspace Editing for Language Model Sequential Editingcited by 8
  26. 2025Revealing and Mitigating Over-Attention in Knowledge Editingcited by 8
  27. 2025MEMIT-Merge: Addressing MEMIT's Key-Value Conflicts in Same-Subject Batch Editing for LLMscited by 6
  28. 2025MindBridge: Scalable and Cross-Model Knowledge Editing via Memory-Augmented Modalitycited by 6
  29. 2025K-Edit: Language Model Editing with Contextual Knowledge Awarenesscited by 5
  30. 2024ComprehendEdit: A Comprehensive Dataset and Evaluation Framework for Multimodal Knowledge Editingcited by 4
  31. 2025FLEKE: Federated Locate-then-Edit Knowledge Editingcited by 2
  32. 2025Constraining Sequential Model Editing with Editing Anchor Compressioncited by 2
  33. 2025LLM Braces: Straightening Out LLM Predictions with Relevant Sub-Updatescited by 2

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  3. 2024RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Driving
  4. 2023DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving
  5. 2025AD-EE: Early Exiting for Fast and Reliable Vision-Language Models in Autonomous Driving
  6. 2024Probing Multimodal LLMs as World Models for Driving
  7. 2024Large Language Models for Human-like Autonomous Driving: A Survey
  8. 2024EMMA: End-to-End Multimodal Model for Autonomous Driving