mlsanityData to 14 Oct 2026

HARGPT: Are LLMs Zero-Shot Human Activity Recognizers?

arXiv 2403.02727 ↗First posted 5 Mar 2024cs.CL cs.AI cs.HCcited by 54

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Abstract (arXiv)

There is an ongoing debate regarding the potential of Large Language Models (LLMs) as foundational models seamlessly integrated with Cyber-Physical Systems (CPS) for interpreting the physical world. In this paper, we carry out a case study to answer the following question: Are LLMs capable of zero-shot human activity recognition (HAR). Our study, HARGPT, presents an affirmative answer by demonstrating that LLMs can comprehend raw IMU data and perform HAR tasks in a zero-shot manner, with only appropriate prompts. HARGPT inputs raw IMU data into LLMs and utilizes the role-play and think step-by-step strategies for prompting. We benchmark HARGPT on GPT4 using two public datasets of different inter-class similarities and compare various baselines both based on traditional machine learning and state-of-the-art deep classification models. Remarkably, LLMs successfully recognize human activities from raw IMU data and consistently outperform all the baselines on both datasets. Our findings indicate that by effective prompting, LLMs can interpret raw IMU data based on their knowledge base, possessing a promising potential to analyze raw sensor data of the physical world effectively.

Key facts. Cited by 54 papers in the map (data through 14 Oct 2026). Builds on 12 of its 22 references that are in the map. First posted on arXiv 5 Mar 2024.

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12 of 22 references.

References · 12

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  4. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  5. 2017Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networkscited by 1,328
  6. 2023Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicinecited by 329
  7. 2024Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Securitycited by 260
  8. 2023ChatGPT: Jack of all trades, master of nonecited by 204
  9. 2015A Random Forest Guided Tourcited by 168
  10. 2024Health-LLM: Large Language Models for Health Prediction via Wearable Sensor Datacited by 66
  11. 2023Penetrative AI: Making LLMs Comprehend the Physical Worldcited by 64
  12. 2024When Large Language Model Agents Meet 6G Networks: Perception, Grounding, and Alignmentcited by 43

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 18; 2025: 20; 2026: 16.

54 papers.

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  1. 2024SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognitioncited by 38
  2. 2024UniMTS: Unified Pre-training for Motion Time Seriescited by 26
  3. 2024DrHouse: An LLM-empowered Diagnostic Reasoning System through Harnessing Outcomes from Sensor Data and Expert Knowledgecited by 24
  4. 2024IoT-LLM: a framework for enhancing Large Language Model reasoning from real-world sensor datacited by 18
  5. 2025AutoIOT: LLM-Driven Automated Natural Language Programming for AIoT Applicationscited by 17
  6. 2025ZARA: Training-Free Motion Time-Series Reasoning via Evidence-Grounded LLM Agentscited by 15
  7. 2024Layout Agnostic Human Activity Recognition in Smart Homes through Textual Descriptions Of Sensor Triggers (TDOST)cited by 13
  8. 2024Large Language Models are Zero-Shot Recognizers for Activities of Daily Livingcited by 13
  9. 2025SensorChat: Answering Qualitative and Quantitative Questions during Long-Term Multimodal Sensor Interactionscited by 11
  10. 2025ProAgent: Harnessing On-Demand Sensory Contexts for Proactive LLM Agent Systems in the Wildcited by 10
  11. 2024Using Large Language Models to Compare Explainable Models for Smart Home Human Activity Recognitioncited by 9
  12. 2024MindGuard: Towards Accessible and Sitgma-free Mental Health First Aid via Edge LLMcited by 7
38 more
  1. 2025RAG-HAR: Retrieval Augmented Generation-based Human Activity Recognitioncited by 7
  2. 2024Large Language Model-Guided Semantic Alignment for Human Activity Recognitioncited by 6
  3. 2024EmbedGenius: Towards Automated Software Development for Generic Embedded IoT Systemscited by 6
  4. 2025Wi-Chat: Large Language Model Powered Wi-Fi Sensingcited by 6
  5. 2025ProMind-LLM: Proactive Mental Health Care via Causal Reasoning with Sensor Datacited by 6
  6. 2025Towards Generalizable Human Activity Recognition: A Surveycited by 6
  7. 2024LightLLM: A Versatile Large Language Model for Predictive Light Sensingcited by 5
  8. 2025Leveraging Large Language Models for Explainable Activity Recognition in Smart Homes: A Critical Evaluationcited by 5
  9. 2025A Survey of Foundation Models for IoT: Taxonomy and Criteria-Based Analysiscited by 5
  10. 2025DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMscited by 5
  11. 2025QuAnTS: Question Answering on Time Seriescited by 5
  12. 2024TransCompressor: LLM-Powered Multimodal Data Compression for Smart Transportationcited by 4
  13. 2024Large Language Models Memorize Sensor Datasets! Implications on Human Activity Recognition Researchcited by 3
  14. 2024Are You Being Tracked? Discover the Power of Zero-Shot Trajectory Tracing with LLMs!cited by 2
  15. 2024SensorBench: Benchmarking LLMs in Coding-Based Sensor Processingcited by 2
  16. 2025MHARFedLLM: Multimodal Human Activity Recognition Using Federated Large Language Modelcited by 2
  17. 2026RAG-HAR+: Towards Cost-Efficient LLM-Based Human Activity Recognition for Edge Deploymentcited by 2
  18. 2025Human Re-ID Meets LVLMs: What can we expect?cited by 1
  19. 2025An LLM-Empowered Low-Resolution Vision System for On-Device Human Behavior Understandingcited by 1
  20. 2025MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answeringcited by 1
  21. 2025SignalLLM: A General-Purpose LLM Agent Framework for Automated Signal Processingcited by 1
  22. 2025Hi-OSCAR: Hierarchical Open-set Classifier for Human Activity Recognitioncited by 1
  23. 2025On-device Large Multi-modal Agent for Human Activity Recognitioncited by 1
  24. 2026AutORAN: LLM-driven Natural Language Programming for Agile xApp Developmentcited by 1
  25. 2026AnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the Wildcited by 1
  26. 2026LLM Agents for Time-Series: A Surveycited by 1
  27. 2024ContextGPT: Infusing LLMs Knowledge into Neuro-Symbolic Activity Recognition Modelscited by 0
  28. 2024AutoLife: Automatic Life Journaling with Smartphones and LLMscited by 0
  29. 2024OV-HHIR: Open Vocabulary Human Interaction Recognition Using Cross-modal Integration of Large Language Modelscited by 0
  30. 2025Adaptive and Robust Data Poisoning Detection and Sanitization in Wearable IoT Systems using Large Language Modelscited by 0
  31. 2026MobiDiary: Autoregressive Action Captioning with Wearable Devices and Wireless Signalscited by 0
  32. 2026FED-HARGPT: A Hybrid Centralized-Federated Approach of a Transformer-based Architecture for Human Context Recognitioncited by 0
  33. 2026ActivityNarrated: An Open-Ended Narrative Paradigm for Wearable Human Activity Understandingcited by 0
  34. 2026Evaluating Visual Prompts with Eye-Tracking Data for MLLM-Based Human Activity Recognitioncited by 0
  35. 2026RF-LEGO: Modularized Signal Processing-Deep Learning Co-Design for RF Sensing via Deep Unrollingcited by 0
  36. 2026TRACE: Temporal Reasoning over Context and Evidence for Activity Recognition in Smart Homescited by 0
  37. 2026Authority Inversion in LLM-Mediated Ubiquitous Systems: When Models Trust Users Over Sensorscited by 0
  38. 2026Closing the Modality Gap in Zero-Shot HAR: Contrastive Training and Separability-Optimized Prototypes on IMU Datacited by 0

50 most cited of 54 All 54 (JSON)