Qualitative focus-group study finds that trustworthiness in AI for peripartum information must be inspectable rather than asserted, yielding four governance themes: social sensemaking support, pluralistic verification, inspectable recourse, and ecosystem-aware integration.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
AnimationDiff is a visual comparison tool that combines contextual scene viewing, overlay/side-by-side modes, filtering, and temporal lenses to help users select among generated 3D character animations.
HCI researchers designed a museum exhibit using feminist data theories to introduce data through a personal, handmade 'hugging_face vibe' distinct from traditional science displays, along with four design choices for creating such vibes.
citing papers explorer
-
"Where is this coming from?" Uncovering Trustworthiness Ideals in AI-powered Peripartum Information Seeking
Qualitative focus-group study finds that trustworthiness in AI for peripartum information must be inspectable rather than asserted, yielding four governance themes: social sensemaking support, pluralistic verification, inspectable recourse, and ecosystem-aware integration.
-
AnimationDiff: A Visual Comparison Tool for Generated 3D Character Animations
AnimationDiff is a visual comparison tool that combines contextual scene viewing, overlay/side-by-side modes, filtering, and temporal lenses to help users select among generated 3D character animations.
-
Designing Vibes in a Science Museum: from @Science to @hugging_face
HCI researchers designed a museum exhibit using feminist data theories to introduce data through a personal, handmade 'hugging_face vibe' distinct from traditional science displays, along with four design choices for creating such vibes.