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GenLine and GenForm: Two Tools for Interacting with Generative Language Models in a Code Editor

Published: 10 October 2021 Publication History

Abstract

A large, generative language model’s output can be influenced through well-designed prompts, or text-based inputs that establish textual patterns that the model replicates in its output [6]. These capabilities create new opportunities for novel interactions with large, generative language models. We present a macro system with two tools that allow users to invoke language model prompts as macros in a code editor. GenLine allows users to execute macros inline as they write code in the editor (e.g., “Make an OK button” produces the equivalent HTML). GenForm provides a form-like interface where the user provides input that is then transformed into multiple pieces of output at the same time (e.g., a description of web code is transformed into HTML, CSS, and JavaScript).

References

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Daniel Adiwardana, Minh-Thang Luong, David R. So, Jamie Hall, Noah Fiedel, Romal Thoppilan, Zi Yang, Apoorv Kulshreshtha, Gaurav Nemade, Yifeng Lu, and Quoc V. Le. 2020. Towards a Human-like Open-Domain Chatbot. arxiv:2001.09977 [cs.CL] Accessed: 2021-08-12.
[4]
Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, and Charles Sutton. 2021. Program Synthesis with Large Language Models. arxiv:2108.07732 [cs.CL] Accessed: 2021-08-13.
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Gwern Branwen. 2020. GPT-3 Creative Fiction. https://www.gwern.net/GPT-3. Accessed: 2021-03-30.
[6]
Tom Brown et al.2020. Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc., 1877–1901.
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Eli Collins and Zoubin Ghahramani. 2021. LaMDA: our breakthrough conversation technology. https://blog.google/technology/ai/lamda/ Accessed: 2021-07-14.
[8]
Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Ian Simon, Curtis Hawthorne, Noam Shazeer, Andrew M. Dai, Matthew D. Hoffman, Monica Dinculescu, and Douglas Eck. 2019. Music Transformer. In International Conference on Learning Representations. https://openreview.net/forum?id=rJe4ShAcF7
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Fabin Rasheed. 2020. Tweet. https://twitter.com/fabinrasheed/status/1284052438392004608. Accessed: 2021-03-30.
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Sharif Shameem. 2020. Tweet. https://twitter.com/sharifshameem/status/1282692481608331265. Accessed: 2021-04-07.

Cited By

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  • (2024)DirectGPT: A Direct Manipulation Interface to Interact with Large Language ModelsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642462(1-16)Online publication date: 11-May-2024
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cover image ACM Conferences
UIST '21 Adjunct: Adjunct Proceedings of the 34th Annual ACM Symposium on User Interface Software and Technology
October 2021
182 pages
ISBN:9781450386555
DOI:10.1145/3474349
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 10 October 2021

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Author Tags

  1. code synthesis
  2. generative models
  3. macros
  4. prompt programming

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  • Demonstration
  • Research
  • Refereed limited

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UIST '21

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Overall Acceptance Rate 842 of 3,967 submissions, 21%

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UIST '24

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Cited By

View all
  • (2024)ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into PrinciplesProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645144(853-868)Online publication date: 18-Mar-2024
  • (2024)A Taxonomy for Human-LLM Interaction Modes: An Initial ExplorationExtended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650786(1-11)Online publication date: 11-May-2024
  • (2024)DirectGPT: A Direct Manipulation Interface to Interact with Large Language ModelsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642462(1-16)Online publication date: 11-May-2024
  • (2024)Deconstructing the Veneer of Simplicity: Co-Designing Introductory Generative AI Workshops with Local EntrepreneursProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642191(1-16)Online publication date: 11-May-2024
  • (2024)Human I/O: Towards a Unified Approach to Detecting Situational ImpairmentsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642065(1-18)Online publication date: 11-May-2024
  • (2024)How Do Data Analysts Respond to AI Assistance? A Wizard-of-Oz StudyProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3641891(1-22)Online publication date: 11-May-2024
  • (2024)A Survey of Natural Language-Based Editing of Low-Code Applications Using Large Language ModelsHuman-Centered Software Engineering10.1007/978-3-031-64576-1_15(243-254)Online publication date: 8-Jul-2024
  • (2023)Cells, Generators, and Lenses: Design Framework for Object-Oriented Interaction with Large Language ModelsProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology10.1145/3586183.3606833(1-18)Online publication date: 29-Oct-2023
  • (2023)GPTeach: Interactive TA Training with GPT-based StudentsProceedings of the Tenth ACM Conference on Learning @ Scale10.1145/3573051.3593393(226-236)Online publication date: 20-Jul-2023
  • (2023)On the Design of AI-powered Code Assistants for NotebooksProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580940(1-16)Online publication date: 19-Apr-2023
  • Show More Cited By

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