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LoRA-Based Cascaded Multimodal Fusion for Action Recognition in Medical Training Environments

This paper presents a cascaded Low-Rank Adaptation (LoRA)-based multimodal fusion framework for action and activity recognition in healthcare-oriented training environments. The proposed architecture combines parameter-efficient modality-specific adaptation with sequential fusion, enabling modalities to be integrated in stages without retraining previously learned components. Rather than assuming a fixed fusion structure, the framework first integrates more closely related modalities and then in

Record details

Published: 13 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Healthcare · Environment
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (13 July 2026), “LoRA-Based Cascaded Multimodal Fusion for Action Recognition in Medical Training Environments,” evidence record 3006, https://ethics.ai/record/3006 (originally published by arXiv cs.AI).

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