Take It, Leave It, or Fix It: Measuring Productivity and Trust in Human-AI Collaboration

28 February 2024

Papers citing "Take It, Leave It, or Fix It: Measuring Productivity and Trust in Human-AI Collaboration"

7 / 7 papers shown

Title
A Framework for Situating Innovations, Opportunities, and Challenges in Advancing Vertical Systems with Large AI Models Gaurav Verma Jiawei Zhou Mohit Chandra Srijan Kumar M. D. Choudhury 53 0 0 03 Apr 2025
Junior Software Developers' Perspectives on Adopting LLMs for Software Engineering: a Systematic Literature Review Samuel Ferino Rashina Hoda John Grundy Christoph Treude 67 0 0 10 Mar 2025
Making Sense of AI Limitations: How Individual Perceptions Shape Organizational Readiness for AI Adoption Thomas Übellacker 45 0 0 21 Feb 2025
Navigating the Unknown: A Chat-Based Collaborative Interface for Personalized Exploratory Tasks Yingzhe Peng Xiaoting Qin Zhiyang Zhang Jue Zhang Qingwei Lin Xu Yang Dongmei Zhang Saravan Rajmohan Qi Zhang 36 3 0 31 Oct 2024
Understanding the Human-LLM Dynamic: A Literature Survey of LLM Use in Programming Tasks Deborah Etsenake Meiyappan Nagappan 38 6 0 01 Oct 2024
Grounded Copilot: How Programmers Interact with Code-Generating Models Shraddha Barke M. James Nadia Polikarpova 164 212 0 30 Jun 2022
Productivity Assessment of Neural Code Completion Albert Ziegler Eirini Kalliamvakou Shawn Simister Ganesh Sittampalam Alice Li Andrew Rice Devon Rifkin E. Aftandilian 102 177 0 13 May 2022