mmExpert: Integrating Large Language Models for Comprehensive mmWave Data Synthesis and Understanding
Millimeter-wave (mmWave) sensing technology holds significant value in human-centric applications, yet the high costs associated with data acquisition and annotation limit its widespread adoption in our daily lives. Concurrently, the rapid evolution of large language models (LLMs) has opened up opportunities for addressing complex human needs. This paper presents mmExpert, an innovative mmWave understanding framework consisting of a data generation flywheel that leverages LLMs to automate the generation of synthetic mmWave radar datasets for specific application scenarios, thereby training models capable of zero-shot generalization in real-world environments. Extensive experiments demonstrate that the data synthesized by mmExpert significantly enhances the performance of downstream models and facilitates the successful deployment of large models for mmWave understanding.
Code (0)
등록된 구현이 없습니다.
Tasks
Zero-shot GeneralizationSimilar Papers 제목 키워드 기반
Integrated Communication and Localization in mmWave Systems
As the fifth-generation (5G) mobile communication system is being commercialized, extensive studies on the evolution of 5G and sixth-generation mobile communication systems have been conducted. Future mobile communicatio…
Can Language Models Understand mmWave Data? Benchmarking Large Language Models for mmWave Radar-Based Human Understanding
Large language models (LLMs) have shown remarkable reasoning and generative capabilities, motivating their use as universal reasoning engines for perception. While modern approaches such as vision-language models (VLMs) …
Question AnsweringIntegrated Monostatic and Bistatic mmWave Sensing
Millimeter-wave (mmWave) signals provide attractive opportunities for sensing due to their inherent geometrical connections to physical propagation channels. Two common modalities used in mmWave sensing are monostatic an…
Survey on Neighbor Discovery and Beam Alignment in mmWave-Enabled UAV Swarm Networks
Millimeter wave (mmWave)-enabled unmanned aerial vehicle (UAV) swarm networks (UAVSNs) can utilize a large spectrum of resources to provide low latency and high data transmission rate. Additionally, owing to the short wa…
4D mmWave Radar in Adverse Environments for Autonomous Driving: A Survey
Autonomous driving systems require accurate and reliable perception. However, adverse environments, such as rain, snow, and fog, can significantly degrade the performance of LiDAR and cameras. In contrast, 4D millimeter-…
Autonomous DrivingSurvey