Generation Probabilities Are Not Enough: Exploring the Effectiveness of
Uncertainty Highlighting in AI-Powered Code Completions

Generation Probabilities Are Not Enough: Exploring the Effectiveness of Uncertainty Highlighting in AI-Powered Code Completions

14 February 2023

Helena Vasconcelos

Jennifer Wortman Vaughan

Papers citing "Generation Probabilities Are Not Enough: Exploring the Effectiveness of Uncertainty Highlighting in AI-Powered Code Completions"

5 / 5 papers shown

Title
CoLadder: Supporting Programmers with Hierarchical Code Generation in Multi-Level Abstraction Ryan Yen Jiawen Zhu Sangho Suh Haijun Xia Jian Zhao 43 14 0 12 Oct 2023
Comparing Traditional and LLM-based Search for Consumer Choice: A Randomized Experiment S. Spatharioti David M. Rothschild D. Goldstein Jake M. Hofman 28 44 0 07 Jul 2023
Exploring the Role of AI Assistants in Computer Science Education: Methods, Implications, and Instructor Perspectives Tianjia Wang Daniel Vargas-Diaz Christopher Brown Yan Chen 22 30 0 05 Jun 2023
AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap Q. V. Liao J. Vaughan 38 158 0 02 Jun 2023
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