Publications

He, J. & Liu, J. (2026). Not All Transparency Is Equal: Source Presentation Effects on Attention, Interaction, and Persuasion in Conversational Search In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval. New York, NY: ACM (CHIIR).

Jiang, T., Li, W., & Liu, J. (2026). Improving data reusability in interactive information retrieval: Insights from the community In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval. New York, NY: ACM (CHIIR).

Dewan, M., Liu, J., & Shah, C. (2026). TRUE: A reproducible framework for LLM-driven relevance judgment in information retrieval In Proceedings of the 19th ACM International Conference on Web Search and Data Mining. Boise, Idaho. 4 pages. (WSDM).

Chen, N., Fang, H., Liu, J., Wei, W., Sakai, T., & Wu, X-M. (2026). Mitigating the threshold priming effect in large language model-based relevance judgments via personality simulation In Proceedings of the 19th ACM International Conference on Web Search and Data Mining. Boise, Idaho. 4 pages. (WSDM).

Jung, Y. J., Liu, J., Nazari, M & Karahan, H. (2025). Empowering children’s maker-based STEM learning through Generative AI in public libraries In Proceedings of the Association for Information Science and Technology. (ASIS&T).

Lei, J., Hu, L., Bu, Y. & Liu, J. (2025). Understanding teams and productivity in information retrieval research: Academia, industry, and cross-community collaborations Journal of Data and Information Science (JDIS).

Liu, J., & Azzopardi, L. (2025). Report on the CHIIR 2024, SIGIR 2024, and SIGIR-AP 2024 tutorials on Characterizing, Evaluating, and Mitigating Cognitive Biases in Interactive and Generative IR In ACM SIGIR Forum (Vol. 59, No. 1, pp. 1-13). New York, NY, USA: ACM.

Yu, R., & Liu, J. (2025). Chat as Learning in Interactive Information Retrieval and Generation In ACM SIGIR Forum (Vol. 59, No. 1, pp. 1-19). New York, NY, USA: ACM.

Jiang, T., Li, W., & Liu, J. (2025). The landscape of data reuse in interactive information retrieval: Motivations, sources, and evaluation of reusability Journal of the Association for Information Science and Technology (JASIST).

Dewan, M., Liu, J., & Shah, C. (2025). LLM-driven usefulness labeling for IR evaluation In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, Padova, Italy.

Chen, N., Liu, J., Fang, H., Luo, Y., Sakai, T., & Wu, X.-M. (2025). Decoy effect in search interaction: Understanding user behavior and measuring system vulnerability ACM Transactions on Information Systems (TOIS).

Liu, J., & He, J. (2025). Boundedly rational searchers interacting with medical misinformation: Characterizing context-dependent decoy effects on credibility and usefulness evaluation in sessions In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR).

Zhang, Y., & Liu, J. (2024). Falling behind again? Characterizing and assessing older adults’ algorithm literacy in interactions with video recommendations Journal of the Association for Information Science and Technology (JASIST).

Jung, Y. J., & Liu, J. (2024). Toward a conceptual framework characterizing the interplay of interest development, information search, and knowledge construction (ISK) in children’s learning Aslib Journal of Information Management.

Wang, B., & Liu, J. (2024). Understanding users’ dynamic perceptions of search gain and cost in sessions: An expectation confirmation model Journal of the Association for Information Science and Technology (JASIST).

Zhang, Y., & Liu, J. (2024). Unpacking older adults' mental models of video recommender systems: A qualitative study In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL).

Chen, N., Liu, J., Dong, X., Liu, Q., Sakai, T., & Wu, X.-M. (2024). AI can be cognitively biased: An exploratory study on threshold priming in LLM-based batch relevance assessment In Proceedings of the 2nd International ACM SIGIR Conference on Information Retrieval in the Asia Pacific (SIGIR-AP).

Azzopardi, L., & Liu, J. (2024). Evaluating cognitive biases in conversational and generative IIR: A tutorial In Proceedings of the ACM SIGIR Conference on Information Retrieval in the Asia Pacific (SIGIR-AP).

Wang, B., & Liu, J. (2024). Cognitively biased users interacting with algorithmically biased results in whole-session search on debated topics In Proceedings of the ACM International Conference on the Theory of Information Retrieval (ICTIR 2024), Washington D.C., USA.

Liu, J., & Azzopardi, L. (2024). Search under Uncertainty: Cognitive Biases and Heuristics – A Tutorial on Testing, Mitigating and Accounting for Cognitive Biases in Search Experiments In Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024), Washington D.C., USA.

Wang, B. (2024). A proactive system for supporting users in interactions with large language models In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2024), Sheffield, UK.

Azzopardi, L., & Liu, J. (2024). Search under uncertainty: Cognitive biases and heuristics – Tutorial on modeling search interaction using behavioral economics In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2024), Sheffield, UK.

Wang, B., Liu, J., Karimnazarov, J., & Thompson, N. (2024). Task supportive and personalized human–large language model interaction: A user study In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2024), Sheffield, UK.

Markwald, M., Liu, J., & Yu, R. (2023). Constructing and meta-evaluating state-aware evaluation metrics for interactive search systems Information Retrieval Journal.

Zhang, Y., & Liu, J. (2023). Deconstructing proxy health information-seeking behavior: A systematic review Library and Information Science Research, 45(3).

Wang, B., & Liu, J. (2023). Investigating the role of in-situ user expectations in Web search Information Processing & Management.

Liu, J. (2023). A behavioral economics approach to interactive information retrieval: Understanding and supporting boundedly rational users Springer Nature.

Wang, B., & Liu, J. (2023). Characterizing and early predicting user performance for adaptive search path recommendation In Proceedings of the Annual Meeting of the Association for Information Science and Technology (ASIS&T).

Best Information Behavior Conference Paper Award (SIG-USE).

Chen, N., Liu, J., & Sakai, T. (2023). A reference-dependent model for Web search evaluation: Understanding and measuring the experience of boundedly rational users In Proceedings of the ACM Web Conference 2023 (TheWebConf2023), Austin, TX, USA.

Liu, J. (2023). A two-sided fairness framework in search and recommendation In Proceedings of the ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2023), Austin, TX, USA.

Lei, J., Bu, Y., & Liu, J. (2023). Information retrieval research in academia and industry: A preliminary analysis of productivity, authorship, impact, and topic distribution In iConference 2023.

Jiang, T., & Liu, J. (2022). Reflection on future directions: A systematic review of reported limitations and solutions in interactive information retrieval user studies Aslib Journal of Information Management.

Liu, J. (2022). Toward Cranfield-inspired reusability assessment in interactive information retrieval evaluation Information Processing & Management, 59(5): 103007.

Liu, J., & Han, F. (2022). 5-4 ≠ 4-3: On the uneven gaps between different levels of graded user satisfaction in interactive information retrieval evaluation In Proceedings of the 56th Hawaii International Conference on System Sciences (HICSS), Maui, HI.

Jung, Y. J., & Liu, J. (2022). Children’s interest, search, and knowledge: A pilot analysis of a STEM maker workshop In Proceedings of the 85th Annual Meeting of the Association for Information Science and Technology (ASIS&T), 59(1).

Best Information Behavior Conference Poster Award (SIG-USE).

Wang, B., & Liu, J. (2022). Investigating the relationship between in-situ user expectations and Web search behavior In Proceedings of the 85th Annual Meeting of the Association for Information Science and Technology (ASIS&T), 59(1).

Liu, J., & Han, F. (2022). Matching search result diversity with user diversity acceptance in Web search sessions In Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Madrid, Spain.

Ghosh, S., & Liu, J. (2022). OUHCIR at the NTCIR-16 Data Search 2 Task In Proceedings of the NTCIR-16 Conference, Tokyo, Japan.

Liu, J., & Shah, C. (2022). Leveraging user interaction signals and task state information in adaptively optimizing usefulness-oriented search sessions In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL), Cologne, Germany.

Brown, T., & Liu, J. (2022). A reference dependence approach to enhancing early prediction of session behavior and satisfaction In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL), Cologne, Germany.

Liu, J. (2021). Deconstructing search tasks in interactive information retrieval: A systematic review of task dimensions and predictors Information Processing & Management, 58(3), 102522.

Liu, J., & Yu, R. (2021). State-aware meta-evaluation of evaluation metrics in interactive information retrieval In Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM).

Liu, J., & Jung, Y. J. (2021). Interest development, knowledge learning, and interactive IR: Toward a state-based approach to search as learning In Proceedings of the 2021 Conference on Human Information Interaction and Retrieval (CHIIR 2021).

Ghosh, S., & Ghosh, S. (2021). Classifying speech acts using multi-channel deep attention network for task-oriented conversational search agents In Proceedings of the 2021 Conference on Human Information Interaction and Retrieval (CHIIR 2021).

Ghosh, S., & Ghosh, S. (2021). “Do users need human-like conversational agents?” – Exploring conversational system design using framework of human needs DESIRES workshop.

Wang, B., & Liu, J. (2021). Extracting the implicit search states from explicit behavioral signals in complex search tasks Proceedings of the Association for Information Science and Technology, 58(1), 854–856.

Sarkar, S., Mitsui, M., Liu, J., & Shah, C. (2020). Implicit information need as explicit problems, help, and behavioral signals Information Processing & Management, 57(2), 102069.

Liu, J., & Han, F. (2020). Investigating reference dependence effects on user search interaction and satisfaction: A behavioral economics perspective In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020).

Liu, J., Sarkar, S., & Shah, C. (2020). Identifying and predicting the states of complex search tasks In Proceedings of the 2020 Conference on Human Information Interaction and Retrieval (CHIIR 2020).