activity
20082023
most citedThe Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users

661 citations · 3.5k across the 73 of their papers we have counts for

collaborators
Showing 2023Show all

6 papers · 1 filter

cs.CY2023★ 1 cited

Food Choice Mimicry on a Large University Campus

Kristina Gligoric, Arnaud Chiolero, Emre Kıcıman +3

Social influence is a strong determinant of food consumption, which in turn influences health. Although consistent observations have been made on the role of social factors in driv…

cs.CY2023★ 5 cited

Accurate Measures of Vaccination and Concerns of Vaccine Holdouts from Web Search Logs

Serina Chang, Adam Fourney, Eric Horvitz

To design effective vaccine policies, policymakers need detailed data about who has been vaccinated, who is holding out, and why. However, existing data in the US are insufficient:…

cs.HC2023★ 3 cited

When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming

Hussein Mozannar, Gagan Bansal, Adam Fourney +1

AI powered code-recommendation systems, such as Copilot and CodeWhisperer, provide code suggestions inside a programmer's environment (e.g., an IDE) with the aim of improving produ…

cs.AI2023★ 33 cited

Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery

Debadutta Dash, Rahul Thapa, Juan M. Banda +15

Despite growing interest in using large language models (LLMs) in healthcare, current explorations do not assess the real-world utility and safety of LLMs in clinical settings. Our…

cs.CL2023★ 521 cited

Capabilities of GPT-4 on Medical Challenge Problems

Harsha Nori, Nicholas King, Scott Mayer McKinney +2

Large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation across various domains, including medicine. We present a com…

cs.LG2023★ 2 cited

Ideal Abstractions for Decision-Focused Learning

Michael Poli, Stefano Massaroli, Stefano Ermon +2

We present a methodology for formulating simplifying abstractions in machine learning systems by identifying and harnessing the utility structure of decisions. Machine learning tas…