T-SHAP stabilizes SHAP attributions temporally for LSTM fall detection, achieving 94.3% accuracy and improved faithfulness on NTU RGB+D dataset.
‘Help Me Help the AI’: Understanding How Explainability Can Support Human-AI Interaction | Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
Interviews and design sessions with cultural newcomers lead to a four-dimension conceptual framework for a mixed-media MR ordering assistant aimed at lowering cultural, linguistic, and cognitive barriers in foreign restaurants.
citing papers explorer
-
Explainable Fall Detection for Elderly Monitoring via Temporally Stable SHAP in Skeleton-Based Human Activity Recognition
T-SHAP stabilizes SHAP attributions temporally for LSTM fall detection, achieving 94.3% accuracy and improved faithfulness on NTU RGB+D dataset.
-
Cultural Newcomers Dining Across Borders: Need-Based Design Envision of Mixed Media Integration in MR for Foreign Menu Understanding and Ordering
Interviews and design sessions with cultural newcomers lead to a four-dimension conceptual framework for a mixed-media MR ordering assistant aimed at lowering cultural, linguistic, and cognitive barriers in foreign restaurants.