Human-Computer Interaction

Interactive Optimization With LLM-Assisted Preference-Based Problem Instantiation

LAPPI uses LLMs to transform vague natural-language preferences into solver-ready optimization problems, enabling an interactive loop for tasks such as trip planning.

Cooperative Design Optimization through Natural Language Interaction

In this work, we propose the concept of cooperative design optimization through natural language. To realize this, we present a novel technique to integrate an LLM with the Bayesian Optimization (BO)-based optimization procedure, enabling designers to intervene through natural language and understand the system’s intentions behind its suggestions.

What Novice Operators See Changes What the Policy Learns: A User Study of Keypoint Hand Visual Representation for Teleoperated Demonstration

What novices see shapes the demonstrations they collect, so the operator's view and the policy's observation are worth designing together.

FairTalk - Facilitating Balanced Participation in Video Conferencing by Implicit Visualization of Predicted Turn-Grabbing Intention

Toward AI-Mediated Avatar-Based Telecommunication: Investigating Visual Impression of Switching Between User- and AI-Controlled Avatars in Video Chat

Our target scenario is a video chat between two people using avatars, where one person uses an auto-switching mechanism to switch between user-controlled and AI-controlled modes. Our study shows that appropriate auto-switching improves the user experience, highlighting the importance of future research in advancing this auto-switching mechanism.