Usimagent: Large language models for simulating search users

E Zhang, X Wang, P Gong, Y Lin, J Mao - Proceedings of the 47th …, 2024 - dl.acm.org
Due to the advantages in the cost-efficiency and reproducibility, user simulation has become
a promising solution to the user-centric evaluation of information retrieval systems …

Users meet clarifying questions: Toward a better understanding of user interactions for search clarification

J Zou, M Aliannejadi, E Kanoulas, MS Pera… - ACM Transactions on …, 2023 - dl.acm.org
The use of clarifying questions (CQs) is a fairly new and useful technique to aid systems in
recognizing the intent, context, and preferences behind user queries. Yet, understanding the …

Investigating reference dependence effects on user search interaction and satisfaction: A behavioral economics perspective

J Liu, F Han - Proceedings of the 43rd international ACM SIGIR …, 2020 - dl.acm.org
How users think, behave, and make decisions when interacting with information retrieval
(IR) systems is a fundamental research problem in the area of Interactive IR. There is …

Constructing better evaluation metrics by incorporating the anchoring effect into the user model

N Chen, F Zhang, T Sakai - Proceedings of the 45th international ACM …, 2022 - dl.acm.org
Models of existing evaluation metrics assume that users are rational decision-makers trying
to pursue maximised utility. However, studies in behavioural economics show that people …

[HTML][HTML] User behavior modeling for web search evaluation

F Zhang, Y Liu, J Mao, M Zhang, S Ma - AI Open, 2020 - Elsevier
Search engines are widely used in our daily life. Batch evaluation of the performance of
search systems to their users has always been an essential issue in the field of information …

A reference-dependent model for web search evaluation: Understanding and measuring the experience of boundedly rational users

N Chen, J Liu, T Sakai - Proceedings of the ACM web conference 2023, 2023 - dl.acm.org
Previous researches demonstrate that users' actions in search interaction are associated
with relative gains and losses to reference points, known as the reference dependence …

Ai can be cognitively biased: An exploratory study on threshold priming in llm-based batch relevance assessment

N Chen, J Liu, X Dong, Q Liu, T Sakai… - Proceedings of the 2024 …, 2024 - dl.acm.org
Cognitive biases are systematic deviations in thinking that lead to irrational judgments and
problematic decision-making, extensively studied across various fields. Recently, large …

State-aware meta-evaluation of evaluation metrics in interactive information retrieval

J Liu, R Yu - Proceedings of the 30th ACM international conference …, 2021 - dl.acm.org
In interactive IR (IIR), users often seek to achieve different goals (eg exploring a new topic,
finding a specific known item) at different search iterations and thus may evaluate system …