102 citations · 144 across the 7 of their papers we have counts for
6 papers · 1 filter
Believing Anthropomorphism: Examining the Role of Anthropomorphic Cues on Trust in Large Language Models
Michelle Cohn, Mahima Pushkarna, Gbolahan O. Olanubi +4
People now regularly interface with Large Language Models (LLMs) via speech and text (e.g., Bard) interfaces. However, little is known about the relationship between how users anth…
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
Minsuk Kahng, Ian Tenney, Mahima Pushkarna +7
Automatic side-by-side evaluation has emerged as a promising approach to evaluating the quality of responses from large language models (LLMs). However, analyzing the results from…
ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles
Savvas Petridis, Ben Wedin, James Wexler +5
Large language model (LLM) prompting is a promising new approach for users to create and customize their own chatbots. However, current methods for steering a chatbot's outputs, su…
Investigating How Practitioners Use Human-AI Guidelines: A Case Study on the People + AI Guidebook
Nur Yildirim, Mahima Pushkarna, Nitesh Goyal +2
Artificial intelligence (AI) presents new challenges for the user experience (UX) of products and services. Recently, practitioner-facing resources and design guidelines have becom…
Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI
Mahima Pushkarna, Andrew Zaldivar, Oddur Kjartansson
As research and industry moves towards large-scale models capable of numerous downstream tasks, the complexity of understanding multi-modal datasets that give nuance to models rapi…
ClinicalVis: Supporting Clinical Task-Focused Design Evaluation
Marzyeh Ghassemi, Mahima Pushkarna, James Wexler +2
Making decisions about what clinical tasks to prepare for is multi-factored, and especially challenging in intensive care environments where resources must be balanced with patient…