mlsanityData to 7 Oct 2026

Integrating Generative Artificial Intelligence in Intelligent Vehicle Systems

arXiv 2305.17137 ↗First posted 15 May 2023cs.AI cs.LGcited by 5

Not on the map. Why?

Abstract (arXiv)

This paper aims to serve as a comprehensive guide for researchers and practitioners, offering insights into the current state, potential applications, and future research directions for generative artificial intelligence and foundation models within the context of intelligent vehicles. As the automotive industry progressively integrates AI, generative artificial intelligence technologies hold the potential to revolutionize user interactions, delivering more immersive, intuitive, and personalised in-car experiences. We provide an overview of current applications of generative artificial intelligence in the automotive domain, emphasizing speech, audio, vision, and multimodal interactions. We subsequently outline critical future research areas, including domain adaptability, alignment, multimodal integration and others, as well as, address the challenges and risks associated with ethics. By fostering collaboration and addressing these research areas, generative artificial intelligence can unlock its full potential, transforming the driving experience and shaping the future of intelligent vehicles.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 17 of its 34 references that are in the map. First posted on arXiv 15 May 2023.

Builds on

17 of 34 references.

References · 17

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  4. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  5. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  6. 2022Training Compute-Optimal Large Language Modelscited by 2,927
  7. 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,722
  8. 2021Improving language models by retrieving from trillions of tokenscited by 1,278
  9. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,176
  10. 2017Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictionscited by 800
  11. 2023Neural Codec Language Models are Zero-Shot Text to Speech Synthesizerscited by 737
  12. 2020Jukebox: A Generative Model for Musiccited by 535
5 more
  1. 2022Phenaki: Variable Length Video Generation From Open Domain Textual Descriptioncited by 475
  2. 2023MusicLM: Generating Music From Textcited by 442
  3. 2023Augmented Language Models: a Surveycited by 398
  4. 2021Demystifying the Draft EU Artificial Intelligence Actcited by 82
  5. 2023AtMan: Understanding Transformer Predictions Through Memory Efficient Attention Manipulationcited by 30

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 3.

5 papers.