96 citations · 129 across the 11 of their papers we have counts for
12 papers
From Words to Widgets for Controllable LLM Generation
Chao Zhang, Yiren Liu, Lunyiu Nie +3
Natural language remains the predominant way people interact with large language models (LLMs). However, users often struggle to precisely express and control subjective preference…
Perspectra: Choosing Your Experts Enhances Critical Thinking in Multi-Agent Research Ideation
Yiren Liu, Viraj Shah, Sangho Suh +3
Recent advances in multi-agent systems (MAS) enable tools for information search and ideation by assigning personas to agents. However, how users can effectively control, steer, an…
YouthSafe: A Youth-Centric Safety Benchmark and Safeguard Model for Large Language Models
Yaman Yu, Yiren Liu, Jacky Zhang +2
Large Language Models (LLMs) are increasingly used by teenagers and young adults in everyday life, ranging from emotional support and creative expression to educational assistance.…
Understanding Generative AI Risks for Youth: A Taxonomy Based on Empirical Data
Yaman Yu, Yiren Liu, Jacky Zhang +2
Generative AI (GAI) is reshaping the way young users engage with technology. This study introduces a taxonomy of risks associated with youth-GAI interactions, derived from an analy…
VicSim: Enhancing Victim Simulation with Emotional and Linguistic Fidelity
Yerong Li, Yiren Liu, Yun Huang
Scenario-based training has been widely adopted in many public service sectors. Recent advancements in Large Language Models (LLMs) have shown promise in simulating diverse persona…
Improving Emotional Support Delivery in Text-Based Community Safety Reporting Using Large Language Models
Yiren Liu, Yerong Li, Ryan Mayfield +1
Emotional support is a crucial aspect of communication between community members and police dispatchers during incident reporting. However, there is a lack of understanding about h…
EvAlignUX: Advancing UX Evaluation through LLM-Supported Metrics Exploration
Qingxiao Zheng, Minrui Chen, Pranav Sharma +4
Evaluating UX in the context of AI's complexity, unpredictability, and generative nature presents unique challenges. How can we support HCI researchers to create comprehensive UX e…
PersonaFlow: Designing LLM-Simulated Expert Perspectives for Enhanced Research Ideation
Yiren Liu, Pranav Sharma, Mehul Jitendra Oswal +2
Generating interdisciplinary research ideas requires diverse domain expertise, but access to timely feedback is often limited by the availability of experts. In this paper, we intr…
CoQuest: Exploring Research Question Co-Creation with an LLM-based Agent
Yiren Liu, Si Chen, Haocong Cheng +5
Developing novel research questions (RQs) often requires extensive literature reviews, especially in interdisciplinary fields. To support RQ development through human-AI co-creatio…
Commonsense-Aware Prompting for Controllable Empathetic Dialogue Generation
Yiren Liu, Halil Kilicoglu
Improving the emotional awareness of pre-trained language models is an emerging important problem for dialogue generation tasks. Although prior studies have introduced methods to i…
Discovering the Hidden Facts of User-Dispatcher Interactions via Text-based Reporting Systems for Community Safety
Yiren Liu, Ryan Mayfield, Yun Huang
Recently, an increasing number of safety organizations in the U.S. have incorporated text-based risk reporting systems to respond to safety incident reports from their community me…
UX Research on Conversational Human-AI Interaction: A Literature Review of the ACM Digital Library
Qingxiao Zheng, Yiliu Tang, Yiren Liu +2
Early conversational agents (CAs) focused on dyadic human-AI interaction between humans and the CAs, followed by the increasing popularity of polyadic human-AI interaction, in whic…