AromaGen generates real-time custom aromas from free-form text or visual inputs via multimodal LLM mapping to 12 odorants, matching or exceeding human mixtures after iterative refinement in a 26-person study.
Karen Shen and Dongwook Yoon
4 Pith papers cite this work. Polarity classification is still indexing.
citation-role summary
citation-polarity summary
fields
cs.HC 4years
2026 4verdicts
UNVERDICTED 4roles
background 3polarities
background 3representative citing papers
Agency in sustained human-AI chatbot talks emerges as co-constructed turn-by-turn through boundary-setting and intention-steering, organized in a new 3-by-4 framework of actors and actions.
Interviews with 18 older adults show that AI safety interventions frequently disrupt emotional support-seeking, leading to calls for designs that respect users' pacing and preserve agency.
A qualitative study with 22 creative writers finds that the reflective value of AI refusals depends on alignment with users' situational thinking phases, cognitive beliefs, and views of AI roles.
citing papers explorer
-
AromaGen: Interactive Generation of Rich Olfactory Experiences with Multimodal Language Models
AromaGen generates real-time custom aromas from free-form text or visual inputs via multimodal LLM mapping to 12 odorants, matching or exceeding human mixtures after iterative refinement in a 26-person study.
-
Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interaction
Agency in sustained human-AI chatbot talks emerges as co-constructed turn-by-turn through boundary-setting and intention-steering, organized in a new 3-by-4 framework of actors and actions.
-
Designing with Tensions: Older Adults' Emotional Support-Seeking Under System-Level Constraints in Conversational AI
Interviews with 18 older adults show that AI safety interventions frequently disrupt emotional support-seeking, leading to calls for designs that respect users' pacing and preserve agency.
-
Beyond Compliance: How AI Could Help Creative Writers by Refusing Them
A qualitative study with 22 creative writers finds that the reflective value of AI refusals depends on alignment with users' situational thinking phases, cognitive beliefs, and views of AI roles.