mlsanityData to 7 Oct 2026

mmExpert: Integrating Large Language Models for Comprehensive mmWave Data Synthesis and Understanding

arXiv 2509.16521 ↗First posted 20 Sep 2025cs.LGcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 14 of its 34 references that are in the map. First posted on arXiv 20 Sep 2025.

Builds on

14 of 34 references.

References · 14

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  4. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  5. 2018Representation Learning with Contrastive Predictive Codingcited by 7,662
  6. 2020Scaling Laws for Neural Language Modelscited by 6,411
  7. 2024Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonecited by 1,883
  8. 2023CogVLM: Visual Expert for Pretrained Language Modelscited by 704
  9. 2016Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Imagecited by 692
  10. 2023PointLLM: Empowering Large Language Models to Understand Point Cloudscited by 326
  11. 2024RF-Diffusion: Radio Signal Generation via Time-Frequency Diffusioncited by 41
  12. 2023A Survey of mmWave-based Human Sensing: Technology, Platform and Applicationscited by 19
2 more
  1. 2021An Overview of Human Activity Recognition Using Wearable Sensors: Healthcare and Artificial Intelligencecited by 11
  2. 2024G3R: Generating Rich and Fine-grained mmWave Radar Data from 2D Videos for Generalized Gesture Recognitioncited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

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  1. 2026Can Language Models Understand mmWave Data? Benchmarking Large Language Models for mmWave Radar-Based Human Understanding
  2. 2025M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models
  3. 2025BeamLLM: Vision-Empowered mmWave Beam Prediction with Large Language Models
  4. 2026RadarTwin: Scene-Specific mmWave Radar Simulation and Learning for Mobile Indoor Perception
  5. 2026Teaching Foundation Models to Read mmWave: Pose-Guided Kinematic Representation for Human Behavior Understanding
  6. 2026RAGent: Physics-Aware Agentic Reasoning for Training-Free mmWave Human Activity Recognition
  7. 2026Enwar 3.0: An Agentic Multi-Modal LLM Orchestrator for Situation-Aware Beamforming, Blockage Prediction, and Handover Management
  8. 2025Diffusion-Based mmWave Radar Point Cloud Enhancement Driven by Range Images