This paper presents an AI-generated review of Vision-Language-Action (VLA) models, summarizing key methodologies, findings, and future directions. The content is produced using large language models (LLMs) and is intended only for demonstration purposes. This work does not represent original research, but highlights how AI can help automate literature reviews. As AI-generated content becomes more prevalent, ensuring accuracy, reliability, and proper synthesis remains a challenge. Future research will focus on developing a structured framework for AI-assisted literature reviews, exploring techniques to enhance citation accuracy, source credibility, and contextual understanding. By examining the potential and limitations of LLM in academic writing, this study aims to contribute to the broader discussion of integrating AI into research workflows. This work serves as a preliminary step toward establishing systematic approaches for leveraging AI in literature review generation, making academic knowledge synthesis more efficient and scalable.
@article{arxiv.2502.06851,
title = {Survey on Vision-Language-Action Models},
author = {Adilzhan Adilkhanov and Amir Yelenov and Assylkhan Seitzhanov and Ayan Mazhitov and Azamat Abdikarimov and Danissa Sandykbayeva and Daryn Kenzhebek and Dinmukhammed Mukashev and Ilyas Umurbekov and Jabrail Chumakov and Kamila Spanova and Karina Burunchina and Madina Yergibay and Margulan Issa and Moldir Zabirova and Nurdaulet Zhuzbay and Nurlan Kabdyshev and Nurlan Zhaniyar and Rasul Yermagambet and Rustam Chibar and Saltanat Seitzhan and Soibkhon Khajikhanov and Tasbolat Taunyazov and Temirlan Galimzhanov and Temirlan Kaiyrbay and Tleukhan Mussin and Togzhan Syrymova and Valeriya Kostyukova and Yerkebulan Massalim and Yermakhan Kassym and Zerde Nurbayeva and Zhanat Kappassov},
journal= {arXiv preprint arXiv:2502.06851},
year = {2025}
}
Comments
arXiv admin note: This submission has been withdrawn due to serious violation of arXiv policies for acceptable submissions