arXiv:2606. 24635v1 Announce Type: cross Abstract: Traditional visual data storytelling relies on binary graphics that depict two simplified groups in conflict.
arXiv:2606. 05178v1 Announce Type: cross Abstract: As AI-driven product development accelerates, the bottleneck is shifting from how we build to what we build.
arXiv:2606. 28294v1 Announce Type: new Abstract: Preference-based alignment often struggles to capture the reasoning that underlies human judgments.
arXiv:2601. 11072v1 Announce Type: cross Abstract: Within journalistic editorial processes, disclosing AI usage is currently limited to simplistic labels, which misses the nuance of how humans and AI collaborated on a news article.
arXiv:2606. 00370v1 Announce Type: cross Abstract: Diverse genomics data, scientific questions, and analysis tasks typically demand highly specialized visualizations.
arXiv:2607. 25911v1 Announce Type: cross Abstract: Annotation is among the most demanding visualization tasks to automate, as it simultaneously requires correctly navigating visual, semantic, and stylistic constraints.
arXiv:2608. 10186v1 Announce Type: cross Abstract: LLMs are increasingly deployed in settings that require collective reasoning on complex, value-laden problems.
arXiv:2607. 10628v1 Announce Type: cross Abstract: We present Anamnesis, an interactive system for demographically controllable survey simulation using large language models.
arXiv:2608. 03910v1 Announce Type: new Abstract: As AI systems are deployed across increasingly diverse social contexts, alignment can no longer be framed as the optimization of a single, unified set of values.
arXiv:2606. 11835v1 Announce Type: cross Abstract: Collecting participants' lived experiences is central to design research.
arXiv:2606. 26614v1 Announce Type: cross Abstract: Large language model (LLM) agents enable natural language interaction for scientific visualization (SciVis).
arXiv:2607. 27232v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly shaping how we consume information and form our worldview.
arXiv:2606. 09848v1 Announce Type: cross Abstract: As generative and agentic AI becomes embedded in everyday products, practitioners face a persistent challenge: how to design human-AI coordination -- the ongoing mutual adjustment between users and AI systems as mediate through interfaces-that supports usability, trust, and safety.