most citedA Survey on Federated Learning in Human Sensing

2 citations · 3 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG2026

TrustmeWatcher: An Application for Workplace Micro-Sensing and Explainable Well-Being Feedback

Chengyu Yu, Leon Jacopo Costa, Zoja Anžur +6

Workplace sensing studies combine long-running behaviour traces with self-reports, yet the tools that collect those data often sit apart from the interface that returns results. We…

cs.AI2026

Hallucination Across the Reasoning Lifecycle: Interface Visibility, Causal Evidence, and Release Control in Large Reasoning Models

Zhe Yu, Mohan Li, Lei Yu +6

Reasoning errors can propagate into later decisions and memory. This survey synthesizes 312 papers and first-party reports on text-based reasoning hallucinations around three quest…

cs.LG2026

Federated Learning with Profile Mapping under Distribution Shifts and Drifts

Mohan Li, Dario Fenoglio, Martin Gjoreski +1

Federated Learning (FL) enables decentralized model training across clients without sharing raw data, but its performance degrades under real-world data heterogeneity. Existing met…

cs.LG2026

Federated Concept-Based Models: Interpretable models with distributed supervision

Dario Fenoglio, Arianna Casanova, Francesco De Santis +6

Concept-based Models (CMs) enhance interpretability in deep learning by grounding predictions in human-understandable concepts. However, concept annotations are costly and rarely a…

cs.LG2025★ 1 cited

Multi-Frequency Federated Learning for Human Activity Recognition Using Head-Worn Sensors

Dario Fenoglio, Mohan Li, Davide Casnici +5

Human Activity Recognition (HAR) benefits various application domains, including health and elderly care. Traditional HAR involves constructing pipelines reliant on centralized use…

cs.LG2025

FLUX: Efficient Descriptor-Driven Clustered Federated Learning under Arbitrary Distribution Shifts

Dario Fenoglio, Mohan Li, Pietro Barbiero +3

Federated Learning (FL) enables collaborative model training across multiple clients while preserving data privacy. Traditional FL methods often use a global model to fit all clien…

cs.LG2025★ 2 cited

A Survey on Federated Learning in Human Sensing

Mohan Li, Martin Gjoreski, Pietro Barbiero +4

Human Sensing, a field that leverages technology to monitor human activities, psycho-physiological states, and interactions with the environment, enhances our understanding of huma…