31 citations · 58 across the 30 of their papers we have counts for
9 papers · 1 filter
Who Gets Recommended? Investigating Gender, Race, and Country Disparities in Paper Recommendations from Large Language Models
Yifan Tian, Yixin Liu, Yi Bu +1
This paper investigates the performance of several representative large models in the tasks of literature recommendation and explores potential biases in research exposure. The res…
The Landscape of Data Reuse in Interactive Information Retrieval: Motivations, Sources, and Evaluation of Reusability
Tianji Jiang, Wenqi Li, Jiqun Liu
Sharing and reusing research data can effectively reduce redundant efforts in data collection and curation, especially for small labs and research teams conducting human-centered s…
The Decoy Dilemma in Online Medical Information Evaluation: A Comparative Study of Credibility Assessments by LLM and Human Judges
Jiqun Liu, Jiangen He
Can AI be cognitively biased in automated information judgment tasks? Despite recent progresses in measuring and mitigating social and algorithmic biases in AI and large language m…
AI Can Be Cognitively Biased: An Exploratory Study on Threshold Priming in LLM-Based Batch Relevance Assessment
Nuo Chen, Jiqun Liu, Xiaoyu Dong +3
Cognitive biases are systematic deviations in thinking that lead to irrational judgments and problematic decision-making, extensively studied across various fields. Recently, large…
Understanding Teams and Productivity in Information Retrieval Research (2000-2018): Academia, Industry, and Cross-Community Collaborations
Jiaqi Lei, Liang Hu, Yi Bu +1
Previous researches on the Information retrieval (IR) field have focused on summarizing progress and synthesizing knowledge and techniques from individual studies and data-driven e…
Report on the Workshop on Simulations for Information Access (Sim4IA 2024) at SIGIR 2024
Timo Breuer, Christin Katharina Kreutz, Norbert Fuhr +15
This paper is a report of the Workshop on Simulations for Information Access (Sim4IA) workshop at SIGIR 2024. The workshop had two keynotes, a panel discussion, nine lightning talk…
Decoy Effect In Search Interaction: Understanding User Behavior and Measuring System Vulnerability
Nuo Chen, Jiqun Liu, Hanpei Fang +3
This study examines the decoy effect's underexplored influence on user search interactions and methods for measuring information retrieval (IR) systems' vulnerability to this effec…
Cognitively Biased Users Interacting with Algorithmically Biased Results in Whole-Session Search on Debated Topics
Ben Wang, Jiqun Liu
When interacting with information retrieval (IR) systems, users, affected by confirmation biases, tend to select search results that confirm their existing beliefs on socially sign…
Task Supportive and Personalized Human-Large Language Model Interaction: A User Study
Ben Wang, Jiqun Liu, Jamshed Karimnazarov +1
Large language model (LLM) applications, such as ChatGPT, are a powerful tool for online information-seeking (IS) and problem-solving tasks. However, users still face challenges in…