6 citations · 16 across the 8 of their papers we have counts for
4 papers · 1 filter
Need Help? Designing Proactive AI Assistants for Programming
Valerie Chen, Alan Zhu, Sebastian Zhao +3
While current chat-based AI assistants primarily operate reactively, responding only when prompted by users, there is significant potential for these systems to proactively assist…
The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers
Hussein Mozannar, Valerie Chen, Mohammed Alsobay +7
Evaluation of large language models for code has primarily relied on static benchmarks, including HumanEval (Chen et al., 2021), or more recently using human preferences of LLM res…
A Data-Centric Approach To Generate Faithful and High Quality Patient Summaries with Large Language Models
Stefan Hegselmann, Shannon Zejiang Shen, Florian Gierse +3
Patients often face difficulties in understanding their hospitalizations, while healthcare workers have limited resources to provide explanations. In this work, we investigate the…
Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study
Niklas Mannhardt, Elizabeth Bondi-Kelly, Barbara Lam +10
Large language models (LLMs) have immense potential to make information more accessible, particularly in medicine, where complex medical jargon can hinder patient comprehension of…