Xinru Wang

schoolPurdue Universitybar_chart#1451 Global Rank

Total Papers

HCI Rank

#1451

Research Areas

Years Active

Recent Publications

Less or More: Towards Glanceable Explanations for LLM Recommendations Using Ultra-Small Devices

Large Language Models (LLMs) have shown remarkable potential in recommending everyday actions as personal AI assistants, while Explainable AI (XAI) techniques are being increasingly utilized to help users understand why a recommendation is given. Personal AI assistants today are often located on ultra-small devices su…

CHI '253rd AuthorHonorable MentionHuman-LLM Collaboration +1

Towards Human-AI Deliberation: Design and Evaluation of LLM-Empowered Deliberative AI for AI-Assisted Decision-Making

Traditional AI-assisted decision-making systems often provide fixed recommendations that users must either accept or reject entirely, limiting meaningful interaction—especially in cases of disagreement. To address this, we introduce Human-AI Deliberation, an approach inspired by human deliberation theories that enable…

CHI '242nd AuthorExplainable AI (XAI) +1

"Are You Really Sure?'' Understanding the Effects of Human Self-Confidence Calibration in AI-Assisted Decision Making

In AI-assisted decision-making, it is crucial but challenging for humans to achieve appropriate reliance on AI. This paper approaches this problem from a human-centered perspective, "human self-confidence calibration". We begin by proposing an analytical framework to highlight the importance of calibrated human self-c…

CHI '241st AuthorHuman-LLM Collaboration +1

Human-LLM Collaborative Annotation Through Effective Verification of LLM Labels

Large language models (LLMs) have shown remarkable performance across various natural language processing (NLP) tasks, indicating their significant potential as data annotators. Although LLM-generated annotations are more cost-effective and efficient to obtain, they are often erroneous for complex or domain-specific t…

CHI '233rd AuthorExplainable AI (XAI) +1

Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness Likelihood to Promote Appropriate Trust in AI-Assisted Decision-Making

In AI-assisted decision-making, it is critical for human decision-makers to know when to trust AI and when to trust themselves. However, prior studies calibrated human trust only based on AI confidence indicating AI's correctness likelihood (CL) but ignored humans' CL, hindering optimal team decision-making. To mitiga…

CHI '231st AuthorExplainable AI (XAI) +1

Watch Out For Updates: Understanding the Effects of Model Explanation Updates in AI-Assisted Decision Making

AI explanations have been increasingly used to help people better utilize AI recommendations in AI-assisted decision making. While AI explanations may change over time due to updates of the AI model, little is known about how these changes may affect people’s perceptions and usage of the model. In this paper, we study…

IUI '211st AuthorExplainable AI (XAI) +1

Are Explanations Helpful? A Comparative Study of the Effects of Explanations in AI-Assisted Decision-Making

This paper contributes to the growing literature in empirical evaluation of explainable AI (XAI) methods by presenting a comparison on the effects of a set of established XAI methods in AI-assisted decision making. Specifically, based on our review of previous literature, we highlight three desirable properties that i…

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