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20242026
most citedCUI@CHI 2024: Building Trust in CUIs-From Design to Deployment

8 citations · 11 across the 11 of their papers we have counts for

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7 papers · 1 filter

cs.HC2026

Deflecting the Value Compass: Interacting with Large Language Models Temporarily Shifts Human Value Priorities Toward Personal Focus

Hasibur Rahman, Malak Sadek, Smit Desai

Large language models increasingly support decisions where values are in tension, yet little is known about whether interacting with them changes which values users prioritize. In…

cs.HC2026

Annie, Are You Okay? How Style- and Context-Based Personalization Shape AI-Assisted Decision-Making

Hasibur Rahman, Benjamin R. Cowan, Smit Desai

As people turn to generative AI for financial advice, these systems can personalize how they communicate and what they say. Whether these forms of personalization shape decisions d…

cs.CL2026

Misalignment Has a Personality: A Big Five Account of Emergent Misalignment

Hasibur Rahman, Smit Desai

Fine-tuning a language model on data containing a narrow flaw, such as insecure code or incorrect mathematical answers, can cause broad misalignment through a mechanism that remain…

cs.CL2026

Behavior-Adaptive Conversational Agents: Toward a Fluid Personality Framework

Hasibur Rahman, Smit Desai

Large language model (LLM)-based conversational agents (CAs) are now ubiquitous, creating new opportunities for AI-mediated behavior change. Their capacity to project nuanced perso…

cs.HC2026

Explanations as Dialogues: Toward Human-Centered Conversational Explainable AI

Niharika Mathur, Smit Desai

As AI systems become increasingly conversational, a gap emerges wherein explanations are studied as static artifacts, yet in practice, are experienced as dialogue. In this provocat…

cs.HC2026

Tell Me Why, When, and How: Effects of Personality, Evidence, and Context on Older Adults' Perceptions of Conversational AI Explanations

Niharika Mathur, Hasibur Rahman, Smit Desai

Large Language Model-based voice assistants (LLM-VAs) have shown potential to support older adults aging in place through proactive reminders, health information, and everyday assi…

cs.HC2026

"Who wants to be nagged by AI?": Investigating the Effects of Agreeableness on Older Adults' Perception of LLM-Based Voice Assistants' Explanations

Niharika Mathur, Hasibur Rahman, Smit Desai

LLM-based voice assistants (VAs) increasingly support older adults aging in place, yet how an assistant's agreeableness shapes explanation perception remains underexplored. We cond…