# Recent Advances in Transformer and Large Language Models for UAV Applications

arXiv: https://arxiv.org/abs/2508.11834 · HTML: https://mlsanity.com/paper/2508.11834/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 49 of its 202 references that are in the map.
- First posted on arXiv 15 Aug 2025.

## Builds on (most cited first, 30 of 49)

- [Flamingo: a Visual Language Model for Few-Shot Learning](https://mlsanity.com/paper/2204.14198/) (2022)
- [BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation](https://mlsanity.com/paper/2201.12086/) (2022)
- [ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks](https://mlsanity.com/paper/1908.02265/) (2019)
- [An Empirical Study of Training Self-Supervised Vision Transformers](https://mlsanity.com/paper/2104.02057/) (2021)
- [TinyBERT: Distilling BERT for Natural Language Understanding](https://mlsanity.com/paper/1909.10351/) (2019)
- [MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer](https://mlsanity.com/paper/2110.02178/) (2021)
- [Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulation](https://mlsanity.com/paper/2209.05451/) (2022)
- [S4L: Self-Supervised Semi-Supervised Learning](https://mlsanity.com/paper/1905.03670/) (2019)
- [Small Language Models: Survey, Measurements, and Insights](https://mlsanity.com/paper/2409.15790/) (2024)
- [Cross Modal Transformer: Towards Fast and Robust 3D Object Detection](https://mlsanity.com/paper/2301.01283/) (2023)
- [TCTrack: Temporal Contexts for Aerial Tracking](https://mlsanity.com/paper/2203.01885/) (2022)
- [SVFormer: Semi-supervised Video Transformer for Action Recognition](https://mlsanity.com/paper/2211.13222/) (2022)
- [A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization](https://mlsanity.com/paper/2201.09206/) (2022)
- [Automatic Speech Recognition using Advanced Deep Learning Approaches: A survey](https://mlsanity.com/paper/2403.01255/) (2024)
- [UAVs Meet LLMs: Overviews and Perspectives Toward Agentic Low-Altitude Mobility](https://mlsanity.com/paper/2501.02341/) (2025)
- [LLMDet: A Third Party Large Language Models Generated Text Detection Tool](https://mlsanity.com/paper/2305.15004/) (2023)
- [FedTP: Federated Learning by Transformer Personalization](https://mlsanity.com/paper/2211.01572/) (2022)
- [Deep Transfer Learning for Automatic Speech Recognition: Towards Better Generalization](https://mlsanity.com/paper/2304.14535/) (2023)
- [Tracker Meets Night: A Transformer Enhancer for UAV Tracking](https://mlsanity.com/paper/2303.10951/) (2023)
- [Federated Learning for Computer Vision](https://mlsanity.com/paper/2308.13558/) (2023)
- [Improving Cross-modal Alignment for Text-Guided Image Inpainting](https://mlsanity.com/paper/2301.11362/) (2023)
- [Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review](https://mlsanity.com/paper/2304.10550/) (2023)
- [Transformers and Large Language Models for Efficient Intrusion Detection Systems: A Comprehensive Survey](https://mlsanity.com/paper/2408.07583/) (2024)
- [Sim2Air - Synthetic aerial dataset for UAV monitoring](https://mlsanity.com/paper/2110.05145/) (2021)
- [Siamese Transformer Pyramid Networks for Real-Time UAV Tracking](https://mlsanity.com/paper/2110.08822/) (2021)
- [OmniVec2 -- A Novel Transformer based Network for Large Scale Multimodal and Multitask Learning](https://mlsanity.com/paper/2507.13364/) (2025)
- [Large Language Model Based Multi-Objective Optimization for Integrated Sensing and Communications in UAV Networks](https://mlsanity.com/paper/2410.05062/) (2024)
- [FlockGPT: Guiding UAV Flocking with Linguistic Orchestration](https://mlsanity.com/paper/2405.05872/) (2024)
- [Anomaly Detection in Aerial Videos with Transformers](https://mlsanity.com/paper/2209.13363/) (2022)
- [Pruning One More Token is Enough: Leveraging Latency-Workload Non-Linearities for Vision Transformers on the Edge](https://mlsanity.com/paper/2407.05941/) (2024)

## Built on by (most cited first, 3 of 3)

- [Large Language Model-Assisted UAV Operations and Communications: A Multifaceted Survey and Tutorial](https://mlsanity.com/paper/2602.19534/) (2026)
- [An LLM-Agnostic, MAVLink-Based Drone Command and Control Interface and Agentic Harness Using the Model Context Protocol](https://mlsanity.com/paper/2601.15486/) (2026)
- [Deep Learning Perspective of Scene Understanding in Autonomous Robots](https://mlsanity.com/paper/2512.14020/) (2025)

## Abstract (arXiv)

The rapid advancement of Transformer-based models has reshaped the landscape of uncrewed aerial vehicle (UAV) systems by enhancing perception, decision-making, and autonomy. This review paper systematically categorizes and evaluates recent developments in Transformer architectures applied to UAVs, including attention mechanisms, CNN-Transformer hybrids, reinforcement learning Transformers, and large language models (LLMs). Unlike previous surveys, this work presents a unified taxonomy of Transformer-based UAV models, highlights emerging applications such as precision agriculture and autonomous navigation, and provides comparative analyses through structured tables and performance benchmarks. The paper also reviews key datasets, simulators, and evaluation metrics used in the field. Furthermore, it identifies existing gaps in the literature, outlines critical challenges in computational efficiency and real-time deployment, and offers future research directions. This comprehensive synthesis aims to guide researchers and practitioners in understanding and advancing Transformer-driven UAV technologies.