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20242026
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cs.HC2026

Overseeing Agents Without Constant Oversight: Challenges and Opportunities

Madeleine Grunde-McLaughlin, Hussein Mozannar, Maya Murad +3

To enable human oversight, agentic AI systems often provide a trace of reasoning and action steps. Designing traces to have an informative, but not overwhelming, level of detail re…

cs.HC2025

CodingGenie: A Proactive LLM-Powered Programming Assistant

Sebastian Zhao, Alan Zhu, Hussein Mozannar +3

While developers increasingly adopt tools powered by large language models (LLMs) in day-to-day workflows, these tools still require explicit user invocation. To seamlessly integra…

cs.HC2025

Need Help? Designing Proactive AI Assistants for Programming

Valerie Chen, Alan Zhu, Sebastian Zhao +3

While current chat-based AI assistants primarily operate reactively, responding only when prompted by users, there is significant potential for these systems to proactively assist…

cs.HC2024

Challenges in Human-Agent Communication

Gagan Bansal, Jennifer Wortman Vaughan, Saleema Amershi +5

Remarkable advancements in modern generative foundation models have enabled the development of sophisticated and highly capable autonomous agents that can observe their environment…

cs.HC2024

Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study

Niklas Mannhardt, Elizabeth Bondi-Kelly, Barbara Lam +10

Large language models (LLMs) have immense potential to make information more accessible, particularly in medicine, where complex medical jargon can hinder patient comprehension of…

cs.HC2024

When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming

Hussein Mozannar, Gagan Bansal, Adam Fourney +1

AI powered code-recommendation systems, such as Copilot and CodeWhisperer, provide code suggestions inside a programmer's environment (e.g., an IDE) with the aim of improving produ…