activity
20242026
most citedA Roadmap to Pluralistic Alignment

14 citations · 14 across the 7 of their papers we have counts for

collaborators

8 papers

cs.HC2026

A Scale For Value Alignment In Human-AI Interaction

Lena Hegemann, Steeven Villa, Hyemin Bang +4

Value alignment is a central objective in AI and HCI research, yet no validated instrument measures how users perceive it. This gap hampers the comparison and accumulation of findi…

cs.AI2026

MatrAIx: Simulating the World with 8.3 Billion Persona Agents

Xiaomin Li, Yuexing Hao, Jianheng Hou +90

Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…

cs.AI2026

A Roadmap to Impactful Pluralistic Alignment Research

Elinor Poole-Dayan, Jillian Fisher, Atoosa Kasirzadeh +3

Pluralistic value alignment---the goal of building AI systems that represent and serve diverse human values and perspectives---has emerged as an active research agenda. Yet, there'…

cs.AI2026

Alignment has a Fantasia Problem

Nathanael Jo, Zoe De Simone, Mitchell Gordon +1

In accomplishing complex tasks, human cognition typically progresses from abstract to concrete (e.g., from brainstorming ideas to writing an essay). With the advent of highly capab…

cs.CL2025

MoReBench: Evaluating Procedural and Pluralistic Moral Reasoning in Language Models, More than Outcomes

Yu Ying Chiu, Michael S. Lee, Rachel Calcott +17

As AI systems progress, we rely more on them to make decisions with us and for us. To ensure that such decisions are aligned with human values, it is imperative for us to understan…

cs.CL2024

StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements

Jillian Fisher, Skyler Hallinan, Ximing Lu +3

Authorship obfuscation, rewriting a text to intentionally obscure the identity of the author, is an important but challenging task. Current methods using large language models (LLM…

cs.CL2024

PERSONA: A Reproducible Testbed for Pluralistic Alignment

Louis Castricato, Nathan Lile, Rafael Rafailov +2

The rapid advancement of language models (LMs) necessitates robust alignment with diverse user values. However, current preference optimization approaches often fail to capture the…

cs.AI2024★ 14 cited

A Roadmap to Pluralistic Alignment

Taylor Sorensen, Jared Moore, Jillian Fisher +9

With increased power and prevalence of AI systems, it is ever more critical that AI systems are designed to serve all, i.e., people with diverse values and perspectives. However, a…