19 papers
LLM-Driven Usefulness Judgment for Web Search Evaluation
Mouly Dewan, Jiqun Liu, Aditya Gautam +1
Evaluation is fundamental in optimizing search experiences and supporting diverse user intents in Information Retrieval (IR). Traditional search evaluation methods primarily rely o…
Experiences Build Characters: The Linguistic Origins and Functional Impact of LLM Personality
Xi Wang, Mengdie Zhuang, Jiqun Liu
Human problem-solving is enriched by a diversity of styles and personality traits, yet the development of Large Language Models (LLMs) has largely prioritized uniform performance b…
FrameRef: A Framing Dataset and Simulation Testbed for Modeling Bounded Rational Information Health
Victor De Lima, Jiqun Liu, Grace Hui Yang
Information ecosystems increasingly shape how people internalize exposure to adverse digital experiences, raising concerns about the long-term consequences for information health.…
ECHO: An Open Research Platform for Evaluation of Chat, Human Behavior, and Outcomes
Jiqun Liu, Nischal Dinesh, Ran Yu
ECHO (Evaluation of Chat, Human behavior, and Outcomes) is an open research platform designed to support reproducible, mixed-method studies of human interaction with both conversat…
Seeing to Think? How Source Transparency Design Shapes Interactive Information Seeking and Evaluation in Conversational AI
Jiangen He, Jiqun Liu
Conversational AI systems increasingly function as primary interfaces for information seeking, yet how they present sources to support information evaluation remains under-explored…
Bounded Minds, Generative Machines: Envisioning Conversational AI that Works with Human Heuristics and Reduces Bias Risk
Jiqun Liu
Conversational AI is rapidly becoming a primary interface for information seeking and decision making, yet most systems still assume idealized users. In practice, human reasoning i…