Wearable accelerometry, EDA, and temperature data from 9 students with profound autism, processed with fine-tuned foundation models, enables prediction of challenging behavior episodes up to 10 minutes in advance at AUC-ROC 0.78 in actual classroom sessions.
MM - SHAP : A performance-agnostic metric for measuring multimodal contributions in vision and language models & tasks
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
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VLMs show answer inertia in CoT reasoning and remain influenced by misleading textual cues even with sufficient visual evidence, making CoT an incomplete window into modality reliance.
citing papers explorer
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Prediction of Challenging Behaviors Associated with Profound Autism in a Classroom Setting Using Wearable Sensors
Wearable accelerometry, EDA, and temperature data from 9 students with profound autism, processed with fine-tuned foundation models, enables prediction of challenging behavior episodes up to 10 minutes in advance at AUC-ROC 0.78 in actual classroom sessions.
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Reasoning Dynamics and the Limits of Monitoring Modality Reliance in Vision-Language Models
VLMs show answer inertia in CoT reasoning and remain influenced by misleading textual cues even with sufficient visual evidence, making CoT an incomplete window into modality reliance.