activity
20212026
most citedPosition: Towards Bidirectional Human-AI Alignment

16 citations · 29 across the 11 of their papers we have counts for

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9 papers · 1 filter

cs.HC2026

Too Long to Watch, Too Short to Leave: Designing for Agent Micro-Waits

Kevin Pu, Anh Truong, Michael Terry +3

Agentic systems increasingly carry out complex work, where a single turn routinely runs for minutes. This produces a micro-wait that is too long to watch and too short to leave. In…

cs.HC2026

Compass vs Railway Tracks: Unpacking User Mental Models for Communicating Long-Horizon Work to Humans vs. AI

Savvas Petridis, Michael Xieyang Liu, Alexander J. Fiannaca +2

As AI systems grow increasingly capable of operating for hours or days at a time, users' prompts are transforming into elaborate specifications for the AI to autonomously work on.…

cs.HC2025

Facilitating Longitudinal Interaction Studies of AI Systems

Tao Long, Sitong Wang, Émilie Fabre +14

UIST researchers develop tools to address user challenges. However, user interactions with AI evolve over time through learning, adaptation, and repurposing, making one time evalua…

cs.HC2025★ 7 cited

Gensors: Authoring Personalized Visual Sensors with Multimodal Foundation Models and Reasoning

Michael Xieyang Liu, Savvas Petridis, Vivian Tsai +4

Multimodal large language models (MLLMs), with their expansive world knowledge and reasoning capabilities, present a unique opportunity for end-users to create personalized AI sens…

cs.HC2024★ 16 cited

Position: Towards Bidirectional Human-AI Alignment

Hua Shen, Tiffany Knearem, Reshmi Ghosh +21

Recent advances in general-purpose AI underscore the urgent need to align AI systems with human goals and values. Yet, the lack of a clear, shared understanding of what constitutes…

cs.HC2024★ 1 cited

In Situ AI Prototyping: Infusing Multimodal Prompts into Mobile Settings with MobileMaker

Savvas Petridis, Michael Xieyang Liu, Alexander J. Fiannaca +3

Recent advances in multimodal large language models (LLMs) have made it easier to rapidly prototype AI-powered features, especially for mobile use cases. However, gathering early,…

cs.HC2023★ 1 cited

PromptInfuser: How Tightly Coupling AI and UI Design Impacts Designers' Workflows

Savvas Petridis, Michael Terry, Carrie J. Cai

Prototyping AI applications is notoriously difficult. While large language model (LLM) prompting has dramatically lowered the barriers to AI prototyping, designers are still protot…

cs.HC2023★ 2 cited

ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles

Savvas Petridis, Ben Wedin, James Wexler +5

Large language model (LLM) prompting is a promising new approach for users to create and customize their own chatbots. However, current methods for steering a chatbot's outputs, su…

cs.HC2021★ 1 cited

PopBlends: Strategies for Conceptual Blending with Large Language Models

Sitong Wang, Savvas Petridis, Taeahn Kwon +2

Pop culture is an important aspect of communication. On social media people often post pop culture reference images that connect an event, product or other entity to a pop culture…