1 citations · 1 across the 8 of their papers we have counts for
10 papers
Emulate or Estimate? The Divergent Strengths of Base and Post-Trained Language Models for Opinion Simulation
Seth Grief-Albert, Jessica Bo, Difan Jiao +1
Large language models are increasingly used to simulate human opinions, but prior work reports conflicting results: some studies find promising alignment with human survey data, wh…
Studying People to Study AI: Expert Perspectives on the Epistemic Fit and Barriers of Human Research in AI Safety & Ethics
Jessica Y. Bo, Paula Akemi Aoyagui, Shalaleh Rismani +3
Safety risks of AI are becoming increasingly evident in human interactions with AI technologies. The prominent approaches to evaluating these risks favor technical methods, such as…
What Counts as AI Sycophancy? A Taxonomy and Expert Survey of a Fragmented Construct
Meryl Ye, Lujain Ibrahim, Jessica Y. Bo +5
AI sycophancy has become a prominent concern in large language model (LLM) research. Yet the term lacks a consistent definition and has been applied to behaviors ranging from agree…
Language Models Exhibit Inconsistent Biases Towards Algorithmic Agents and Human Experts
Jessica Y. Bo, Lillio Mok, Ashton Anderson
Large language models are increasingly used in decision-making tasks that require them to process information from a variety of sources, including both human experts and other algo…
Large Language Lovers: Lived Experiences of Negotiating Agency and Platform Control in AI Companionship
Patrick Yung Kang Lee, Jessica Y. Bo, Zixin Zhao +6
Individuals are turning to increasingly anthropomorphic, general-purpose chatbots for AI companionship, rather than roleplay-specific platforms. However, not much is known about ho…
Invisible Saboteurs: Sycophantic LLMs Mislead Novices in Problem-Solving Tasks
Jessica Y. Bo, Majeed Kazemitabaar, Mengqing Deng +2
Sycophancy, the tendency of LLM-based chatbots to express excessive agreement with their users, even when inappropriate, is emerging as a significant risk in human-AI interactions.…
Who's the Leader? Analyzing Novice Workflows in LLM-Assisted Debugging of Machine Learning Code
Jessica Y. Bo, Majeed Kazemitabaar, Emma Zhuang +1
While LLMs are often touted as tools for democratizing specialized knowledge to beginners, their actual effectiveness for improving task performance and learning is still an open q…
Steerable Chatbots: Exploring Personalization Control Interfaces via LLM Activation Steering
Jessica Y. Bo, Tianyu Xu, Ishan Chatterjee +3
Personalizing LLM responses typically requires users to articulate their preferences through prompting, which can be burdensome at cold start and difficult to articulate in natural…
To Rely or Not to Rely? Evaluating Interventions for Appropriate Reliance on Large Language Models
Jessica Y. Bo, Sophia Wan, Ashton Anderson
As Large Language Models become integral to decision-making, optimism about their power is tempered with concern over their errors. Users may over-rely on LLM advice that is confid…
Incremental XAI: Memorable Understanding of AI with Incremental Explanations
Jessica Y. Bo, Pan Hao, Brian Y. Lim
Many explainable AI (XAI) techniques strive for interpretability by providing concise salient information, such as sparse linear factors. However, users either only see inaccurate…