Understanding users' dynamic perceptions of search gain and cost in sessions: An expectation confirmation model Ben Wang, Jiqun Liu asistdl.onlinelibrary.wiley.com/doi/10.1002/as…

Happy to announce that our tutorial "Evaluating Cognitive Biases in Conversational and Generative IIR" w/Leif Azzopardi has been accepted to #SIGIRAP2024. Please join our slack channel ACM SIGIR for more learning materials and discussions: sigir24-searchunderuncertainty-tutorial 😀

How do older adults understand and manage biases in recommender system? Our latest study JASIST uncovers their unique strategies for interacting with personalized content and emphasizes the importance of designing systems that are inclusive to all users: asistdl.onlinelibrary.wiley.com/doi/10.1002/as…

Ever wondered if AI can be tricked like humans? 🤔 Our study dives into cognitive biases in LLMs, and shows that while advanced models outperform humans in assessing medical information, they’re MORE vulnerable to decoy effects. #AI #Bias #Misinformation arxiv.org/abs/2411.15396

How do Interactive IR researchers make the most of shared data? Our interview study uncovers their strategies and challenges in data reuse and reusability evaluation, revealing how it can fuel innovation and collaboration in IR. #DataReuse #IR #OpenScience arxiv.org/abs/2411.15430

Accepted by ACM TOIS: Decoy Effect In Search Interaction: Understanding User Behavior and Measuring System Vulnerability by Nuo Chen, Jiqun Liu, Hanpei Fang, Yuankai Luo, Tetsuya Sakai (酒井哲也) , Xiao-Ming Wu

2024 is 100% complete.

"Decoy Effect in Search Interaction: Understanding User Behavior and Measuring System Vulnerability" by Nuo Chen, Jiqun Liu, Hanpei Fang, Yuankai Luo, Tetsuya Sakai, and Xiao-Ming Wu got accepted in ACM TOIS

10 Brutal Truths That Will Slap You Into Action: 1.

The first rose of spring in my front yard :-)

The next generation of LLMs will give you the answer before you ask the question.