mlsanityData to 7 Oct 2026

On the Design of AI-powered Code Assistants for Notebooks

arXiv 2301.11178 ↗First posted 26 Jan 2023cs.HCcited by 28

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Abstract (arXiv)

AI-powered code assistants, such as Copilot, are quickly becoming a ubiquitous component of contemporary coding contexts. Among these environments, computational notebooks, such as Jupyter, are of particular interest as they provide rich interface affordances that interleave code and output in a manner that allows for both exploratory and presentational work. Despite their popularity, little is known about the appropriate design of code assistants in notebooks. We investigate the potential of code assistants in computational notebooks by creating a design space (reified from a survey of extant tools) and through an interview-design study (with 15 practicing data scientists). Through this work, we identify challenges and opportunities for future systems in this space, such as the value of disambiguation for tasks like data visualization, the potential of tightly scoped domain-specific tools (like linters), and the importance of polite assistants.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Jan 2023.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 11; 2025: 7; 2026: 3.

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  1. 2023OpenAgents: An Open Platform for Language Agents in the Wildcited by 136
  2. 2023Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitationscited by 96
  3. 2023A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challengescited by 75
  4. 2024PromptCharm: Text-to-Image Generation through Multi-modal Prompting and Refinementcited by 61
  5. 2024WaitGPT: Monitoring and Steering Conversational LLM Agent in Data Analysis with On-the-Fly Code Visualizationcited by 38
  6. 2025Assistance or Disruption? Exploring and Evaluating the Design and Trade-offs of Proactive AI Programming Supportcited by 33
  7. 2024Improving Steering and Verification in AI-Assisted Data Analysis with Interactive Task Decompositioncited by 29
  8. 2024Learning Agent-based Modeling with LLM Companions: Experiences of Novices and Experts Using ChatGPT & NetLogo Chatcited by 23
  9. 2024Data Formulator 2: Iterative Creation of Data Visualizations, with AI Transforming Data Along the Waycited by 19
  10. 2024Position: Towards Bidirectional Human-AI Alignmentcited by 15
  11. 2024BISCUIT: Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebookscited by 12
  12. 2024Synthetic Data Generation with Large Language Models for Personalized Community Question Answeringcited by 8
16 more
  1. 2023Why is AI not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytellingcited by 7
  2. 2025VTutor: An Open-Source SDK for Generative AI-Powered Animated Pedagogical Agents with Multi-Media Outputcited by 7
  3. 2024Data Analysis in the Era of Generative AIcited by 6
  4. 2025Human-AI Experience in Integrated Development Environments: A Systematic Literature Reviewcited by 5
  5. 2025Hookpad Aria: A Copilot for Songwriterscited by 4
  6. 2025"My productivity is boosted, but ..." Demystifying Users' Perception on AI Coding Assistantscited by 4
  7. 2025ALMAS: an Autonomous LLM-based Multi-Agent Software Engineering Frameworkcited by 4
  8. 2023SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebookscited by 3
  9. 2024Untangling Knots: Leveraging LLM for Error Resolution in Computational Notebookscited by 2
  10. 2023"With Great Power Comes Great Responsibility!": Student and Instructor Perspectives on the influence of LLMs on Undergraduate Engineering Educationcited by 1
  11. 2023Natural Language based Context Modeling and Reasoning for Ubiquitous Computing with Large Language Models: A Tutorialcited by 1
  12. 2025HiLDe: Intentional Code Generation via Human-in-the-Loop Decodingcited by 1
  13. 2024Predicting the Understandability of Computational Notebooks through Code Metrics Analysiscited by 0
  14. 2026From Adoption to Deployment: A Qualitative Study on AI Integration in Software Development Practicecited by 0
  15. 2026From Overload to Insights: How AI Agents Can Support Scientists in Analyzing Complex Datacited by 0
  16. 2026Point, Revise, Review: Grounded Agentic Analysis in Reactive Notebooks with marimo-lenscited by 0