7 papers
Cost-Aware Optimization for Agentic Query Execution
Lunyiu Nie, Yilin Xia, Yiren Liu +2
Classical query optimization searches over algebraically equivalent plans that differ only in cost. This assumption breaks once LLM-backed operators enter the picture: their placem…
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.…
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…
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…
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…