[2604.00767] ActivityNarrated: An Open-Ended Narrative Paradigm for Wearable Human Activity Understanding

Computer Science > Machine Learning arXiv:2604.00767 (cs) [Submitted on 1 Apr 2026] Title:ActivityNarrated: An Open-Ended Narrative Paradigm for Wearable Human Activity Understanding Authors:Lala Shakti Swarup Ray, Mengxi Liu, Alcina Pinto, Deepika Gurung, Daniel Geissler, Paul Lukowoicz, Bo Zhou View a PDF of the paper titled ActivityNarrated: An Open-Ended Narrative Paradigm for Wearable Human Activity Understanding, by Lala Shakti Swarup Ray and 6 other authors View PDF HTML (experimental) Abstract:Wearable HAR has improved steadily, but most progress still relies on closed-set classification, which limits real-world use. In practice, human activity is open-ended, unscripted, personalized, and often compositional, unfolding as narratives rather than instances of fixed classes. We argue that addressing this gap does not require simply scaling datasets or models. It requires a fundamental shift in how wearable HAR is formulated, supervised, and evaluated. This work shows how to model open-ended activity narratives by aligning wearable sensor data with natural-language descriptions in an open-vocabulary setting. Our framework has three core components. First, we introduce a naturalistic data collection and annotation pipeline that combines multi-position wearable sensing with free-form, time-aligned narrative descriptions of ongoing behavior, allowing activity semantics to emerge without a predefined vocabulary. Second, we define a retrieval-based evaluation framework that...