arXiv Machine Learning

The Impact of Temporal Granularity on Socio-Demographic Inference from Household Load Profiles

arXiv:2606. 03358v1 Announce Type: new Abstract: Smart meter data can reveal sensitive socio-demographic characteristics of households, raising privacy concerns.

arXiv Machine Learning

Jul 20

Behaviour-Conditioned Neural Processes for Adaptive Residential Short-Term Load Forecasting

arXiv:2607. 16168v1 Announce Type: new Abstract: Residential short-term load forecasting (STLF) is challenging because household demand is heterogeneous, temporally variable, and shaped by diverse behavioural routines.

By Ramin Soleimani, Andrea Visentin, Dirk Pesch

arXiv AI

5d ago

DomusFM: A Foundation Model for Event-Based Behavioral Monitoring in Smart-Homes

arXiv:2602. 01910v2 Announce Type: replace Abstract: Smart-home sensor-based behavioral monitoring holds significant potential for healthcare, independent living, and early detection of functional or cognitive changes.

By Michele Fiori, Gabriele Civitarese, Flora D. Salim, Claudio Bettini

llms rag

arXiv AI

Jun 15

A Comparative Study of Deep Learning Architectures for Multi-Horizon Behavioural Forecasting for Mobile Health

arXiv:2606. 14604v1 Announce Type: cross Abstract: Wearable devices and smartphones generate rich behavioural time series that can support proactive health interventions, yet systematic comparisons of modern forecasting architectures for these data are lacking.

By Pavlos Nicolaou, Kleanthis Malialis, Artemis Kontou, Panayiotis Kolios

llms fine-tuning benchmarks

arXiv Machine Learning

Jul 31

HealthCAT: An Interpretable Encoder-only Transformer Framework for Health Indicator Prediction and Temporal Interpretation of Wearable Sensor Data

arXiv:2607. 27635v1 Announce Type: cross Abstract: Wearable sensors continuously capture fine-grained multivariate time-series data, providing opportunities to model behavioural patterns associated with health outcomes.

By Xiaotong Yu, Joshua Y. Kim, HaeJin Lee, Kalina Yacef

llms safety

arXiv AI

Jun 2

Towards a General Intelligence and Interface for Wearable Health Data

arXiv:2605. 22759v2 Announce Type: replace Abstract: While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personalized health insights is challenging.

By Girish Narayanswamy, Maxwell A. Xu, A. Ali Heydari, Samy Abdel-Ghaffar, Marius Guerard, Kara Vaillancourt, Zhihan Zhang, Jake Garrison, Levi Albuquerque, Dimitris Spathis, Hong Yu, Hamid Palangi, Xuhai "Orson" Xu, David G. T. Barrett, Joseph Breda, Jed McGiffin, Yubin Kim, Yuwei Zhang, Naghmeh Rezaei, Samuel Solomon, Karan Ahuja, Tim Althoff, Jake Sunshine, Ming-Zher Poh, Benjamin Yetton, Ari Winbush, Nicholas B. Allen, James M. Rehg, Isaac Galatzer-Levy, Yun Liu, John Hernandez, Anupam Pathak, Conor Heneghan, Yuzhe Yang, Ahmed A. Metwally, Pushmeet Kohli, Mark Malhotra, Shwetak Patel, Xin Liu, Daniel McDuff

llms rag agents

arXiv AI

Jul 14

WattCouncil: Context-Aware Household Energy Scenario Generation With Governed LLMs

arXiv:2607. 10720v1 Announce Type: new Abstract: The accelerating shift toward low-carbon power systems, together with the widespread adoption of behind-the-meter technologies such as rooftop solar and electric vehicles, is placing new operational and analytical demands on electricity grids.

By Mohannad Takrouri, Nicolas M. Cuadrado A., Martin Tak\'a\v{c}

llms agents benchmarks safety

arXiv Machine Learning

Aug 11

Full-Feature versus Limited-Input Machine Learning for Residential Energy Estimation: A Comparative Analysis of RECS and ResStock Under Realistic Input Constraints

arXiv:2608. 09255v1 Announce Type: new Abstract: Residential energy estimates are often needed before detailed envelope characteristics, equipment efficiencies, infiltration, sensor, or billing data are available.

By Aditya Ramnarayan, Fatih Evren, Patti Gunderson, Samuel Rosenberg

benchmarks

arXiv Machine Learning

Aug 4

Paris as a 15-Minute City: An Explainable AI Perspective

arXiv:2608. 00815v1 Announce Type: new Abstract: The 15-minute city promotes access to everyday services within a short walk or bicycle ride, but its relationship with observed mobility remains difficult to quantify.

By Andr\'as J. Moln\'aar, Csaba I. Sidl\'o, Rita R\'onai, Domonkos R\'ozsay

computer-vision

arXiv AI

Jul 20

Scaling Time Series Classification via XAI-Driven Data Reduction

arXiv:2607. 15774v1 Announce Type: cross Abstract: Explainable AI (XAI) for time series has seen significant algorithmic growth, but its utility in providing measurable performance gains for downstream tasks remains under-explored.

By Davide Italo Serramazza, Thach Le Nguyen, Georgiana Ifrim

llms benchmarks safety

arXiv Machine Learning

Jul 14

Inter-Stop Energy Prediction and Causal Driver Quantification for Dual-Source Trolleybuses via a Time-Aware Tabular Deep Learning Architecture

arXiv:2607. 11349v1 Announce Type: cross Abstract: Dual-source trolleybuses alternate between overhead catenary supply and on-board battery operation, creating energy-use patterns driven by route attributes, high-frequency trajectories, and hourly weather.

By Wentao Zeng (School of Management, Foshan University, Foshan, China a School of Management, Foshan University, Foshan, China, School of Mechanical and Electrical Engineering and Automation, Foshan University, Foshan, China), Zijian Huang (School of Artificial Intelligence, South China Normal University, Guangzhou, China), Yiming Bie (School of Transportation, Jilin University, Changchun, China), Jiabin Wu (School of Management, Foshan University, Foshan, China a School of Management, Foshan University, Foshan, China), Jun Gong (Department of Civil Engineering, The University of Hong Kong, Hong Kong, China)

benchmarks

arXiv Machine Learning

Jun 3

RESCAST-100K: A Comprehensive Dataset for Cross-Domain Residential Load and Indoor Temperature Forecasting

arXiv:2606. 02852v1 Announce Type: new Abstract: Accurate short-term forecasting of residential energy load and indoor temperature is essential for home energy management systems, grid-level demand response, and community energy efficiency efforts.

By Jainam Dhruva, Yousaf Raza, A. B. Siddique, Simone Silvestri

llms robotics fine-tuning benchmarks

arXiv AI

5d ago

INSHAPE: Instance-Level Shapelets for Interpretable Time-Series Classification

arXiv:2605. 20088v2 Announce Type: replace-cross Abstract: Discovering shapelets -- i.

By Seongjun Lee, Seokhyun Lee, Changhee Lee

benchmarks safety

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