no code implementations • 14 Feb 2024 • Negar Arabzadeh, Julia Kiseleva, Qingyun Wu, Chi Wang, Ahmed Awadallah, Victor Dibia, Adam Fourney, Charles Clarke
The rapid development in the field of Large Language Models (LLMs) has led to a surge in applications that facilitate collaboration among multiple agents to assist humans in their daily tasks.
1 code implementation • 12 Jun 2023 • Serina Chang, Adam Fourney, Eric Horvitz
We find that holdouts, compared to early adopters matched on covariates, are 69% more likely to click on untrusted news sites.
1 code implementation • 8 Jun 2023 • Hussein Mozannar, Gagan Bansal, Adam Fourney, Eric Horvitz
Using data from 535 programmers, we perform a retrospective evaluation of CDHF and show that we can avoid displaying a significant fraction of suggestions that would have been rejected.
no code implementations • 14 Feb 2023 • Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan
Through a mixed-methods study with 30 programmers, we compare three conditions: providing the AI system's code completion alone, highlighting tokens with the lowest likelihood of being generated by the underlying generative model, and highlighting tokens with the highest predicted likelihood of being edited by a programmer.
no code implementations • 29 Oct 2022 • Victor Dibia, Adam Fourney, Gagan Bansal, Forough Poursabzi-Sangdeh, Han Liu, Saleema Amershi
Large language models have demonstrated great potential to assist programmers in generating code.
1 code implementation • 25 Oct 2022 • Hussein Mozannar, Gagan Bansal, Adam Fourney, Eric Horvitz
However, to fully realize their potential, we must understand how programmers interact with these systems and identify ways to improve that interaction.
1 code implementation • NAACL 2021 • Ahmed Elgohary, Christopher Meek, Matthew Richardson, Adam Fourney, Gonzalo Ramos, Ahmed Hassan Awadallah
We present NL-EDIT, a model for interpreting natural language feedback in the interaction context to generate a sequence of edits that can be applied to the initial parse to correct its errors.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Xinya Du, Ahmed Hassan Awadallah, Adam Fourney, Robert Sim, Paul Bennett, Claire Cardie
We show that leveraging metadata information from web pages can improve the performance of models for answer passage selection/reranking.
no code implementations • 27 Jan 2020 • Maartje ter Hoeve, Robert Sim, Elnaz Nouri, Adam Fourney, Maarten de Rijke, Ryen W. White
Our contributions are three-fold: (1) We first present a survey to understand the space of document-centered assistance and the capabilities people expect in this scenario.