TRUST-CUA @ IUI 2026 brings together the IUI and AI-agent communities to explore how we can build predictable, steerable, and most importantly, trustworthy computer-using agents (CUAs). These agents operate across GUIs, browsers, APIs, and CLIs, and increasingly act as multi-modal collaborators that assist users in completing complex digital tasks.
Segev Shlomov (IBM Research)
Welcome to TRUST-CUA @ IUI 2026
Workshop goals and motivation
Beyond Demos: From impressive prototypes to reliable, trustworthy computer-using agents
Overview of the day's program
Rotem Dror (University of Haifa)
Data Annotations in the Era of Large Language Models
Beyond Task Completion: A Process-Oriented Framework for Evaluating Preference and Value Alignments in Computer-Using Agents
Remote Presentation
Language Model Agents Under Attack: A Cross-Model Benchmark of Profit-Seeking Behaviors in Customer Service
Pre-recorded Presentation
Trust by Design: Trust Calibration Through Non-Advisory Socratic Dialogue in Conversational Agents
Pre-recorded Presentation
Architecting Trust Without Killing Autonomy: Borrowing Microservice Resilience Patterns for Reliable Computer-Using Agents
Remote Presentation
Designing Trustworthy Agentic RAG Systems Through Modality-Separated Interaction and Error-Aware Memory
Remote Presentation
Zero: Towards Reliable Agentic UX for Industrial Dashboards
Remote Presentation
AgentFixer: From Failure Detection to Fix Recommendations in LLM Agentic Systems
Pre-recorded Presentation
An interactive discussion on the future of trustworthy computer-using agents, including:
Reliability and robustness
Human oversight and trust
Evaluation beyond task completion
Future benchmarks and community collaboration
Closing remarks and next steps.
Modern computer-using agents are evolving into generalist, multi-agent systems capable of reasoning across diverse tools and interfaces. They hold tremendous promise for improving productivity, creativity, and automation. However, they also introduce new challenges for reliability, transparency, and user oversight, and despite this potential, real-world business adoption remains limited.
Developing and validating such systems is often slow and costly, especially when safety and compliance are at stake. Even after deployment, ensuring reliability and trustworthiness is difficult: agents can make silent mistakes, repeat past errors, or drift from intended behavior without clear user visibility.
TRUST-CUA @ IUI 2026 addresses these challenges by exploring how to design CUAs that are predictable, auditable, and user-trustable. The workshop focuses on interface and UX paradigms that foster trust, explainability, human-in-the-loop (HITL), and control, as well as evaluation and governance frameworks that ensure accountability in both enterprise and public settings.
By connecting AI, UX, and human-centered design, TRUST-CUA aims to define a roadmap toward reliable, transparent, and production-ready generalist agents that operate safely and effectively across domains.
Jan 10, 2026
Jan 16, 2026
Feb 2, 2026
Rotem Dror - University of Pennsylvania
Jose Cambronero - Microsoft
Nadia Polikarpova - University of California San Diego
Hadar Mulian – IBM research
Eran Yahav - Technion
Rui Dong - University of Michigan
Xinyun Chen - Google
Sergey Zeltyn - IBM Research
Yan Chen - Virginia Tech
Yanju Chen - University of California, Santa Barbara
Lior Limonad - IBM Research
Jiani Huang - University of Pennsylvania
Kobi Gal - Ben-Gurion University
Please send your inquiry to segev.shlomov1@ibm.com