14 citations · 32 across the 17 of their papers we have counts for
6 papers · 1 filter
Whose Guardrail? User Identity Shapes the Effectiveness of Model Disclaimers in Mitigating LLM Political Persuasion
Jillian Fisher, Thomas Richardson, Daniel W. Fisher +3
Politically biased AI can shift users' opinions, yet it remains unclear whether model disclaimers protect against such persuasion. We report a preregistered experiment (N=1,586) ex…
NewsBench: Expert-Grounded Evaluation of Epistemic Quality in AI News Reporting
Matt Wilde, Jillian Fisher, Andrew B. Hall +2
As frontier AI systems increasingly serve as sources of political and current-events information, evaluating the epistemic quality of their responses is now especially consequentia…
Distilling Expert Judgment at Scale
Robbie Goldfarb, Andrew B. Hall, Jillian Fisher +2
Frontier AI models are increasingly deployed on topics where the stakes are high and expert judgment is required, including healthcare, defense, finance, governance, and politics.…
A Roadmap to Impactful Pluralistic Alignment Research
Elinor Poole-Dayan, Jillian Fisher, Atoosa Kasirzadeh +3
Much research on responsible AI aims to change the behavior of AI systems that billions of people use. Pluralistic value alignment---the goal of building AI systems that represent…
Response-Aware User Memory Selection for LLM Personalization
Jillian Fisher, Jennifer Neville, Chan Young Park
A common approach to personalization in large language models (LLMs) is to incorporate a subset of the user memory into the prompt at inference time to guide the model's generation…
FDARxBench: Benchmarking Regulatory and Clinical Reasoning on FDA Generic Drug Assessment
Betty Xiong, Jillian Fisher, Benjamin Newman +5
We introduce an expert curated, real-world benchmark for evaluating document-grounded question-answering (QA) motivated by generic drug assessment, using the U.S. Food and Drug Adm…