RETRACE is introduced, a resilience-guided trait-conditioned framework for subject-independent craving estimation from wearable physiology that reframes craving detection as trait-conditioned physiological interpretation and uses resilience-related subject context to guide inference.
Yi Xiao, Harshit Sharma, D. Bergen-Cico et al.· 0 citations
Parameter-efficient fine-tuning (PEFT) determines not only how many parameters are trained, but also which local directions a model can move in, so similar adapters can affect subgroup losses differently. Since curvature matrices are infeasible to form at adapter scale, scalar summaries such as the Fisher trace are oft...
Wasif Jalal, Sachin Deb, Asif Salekin· 0 citations
FABLE-Therm is introduced, a weakly supervised architecture that preserves localized evidence across body regions, time, and encoder-specific representations until the final decision, and shows that preserving localized evidence supports both accurate sensing and principled analysis of who a model fails and why.
Sachin Deb, Harshit Sharma, Asif Salekin· 0 citations
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