{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T00:48:25Z","timestamp":1774399705216,"version":"3.50.1"},"reference-count":43,"publisher":"Association for Computing Machinery (ACM)","issue":"1","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGIR Forum"],"published-print":{"date-parts":[[2025,6]]},"abstract":"<jats:p>Query performance prediction (QPP) is a key and long-standing task in information retrieval (IR). The task of QPP aims to predict ranking quality without human relevance judgments. The rise of large language models (LLMs) has significantly reshaped the IR research landscape. These advancements call for a timely discussion on how we perform, evaluate and apply QPP in the LLM era. To foster this discussion, we have organised the workshop on QPP at the 47th European Conference on Information Retrieval (ECIR 2025). While LLM-related topics were a major focus, we made sure to keep our workshop open to a broad range of QPP-related research areas. The workshop featured five accepted papers and gathered around 20 participants for a half-day of presentations and interactive discussions. These discussions produced several key insights and directions for future QPP research.<\/jats:p>\n          <jats:p>\n            <jats:bold>Date:<\/jats:bold>\n            10 April 2025.\n          <\/jats:p>\n          <jats:p>\n            <jats:bold>Website:<\/jats:bold>\n            https:\/\/qppworkshop.github.io\/.\n          <\/jats:p>","DOI":"10.1145\/3769733.3769743","type":"journal-article","created":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:04:53Z","timestamp":1760112293000},"page":"1-8","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Report on the 2nd Workshop on Query Performance Prediction and its Applications in the Era of Large Language Models (QPP++ 2025) at ECIR 2025"],"prefix":"10.1145","volume":"59","author":[{"given":"Chuan","family":"Meng","sequence":"first","affiliation":[{"name":"University of Amsterdam, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guglielmo","family":"Faggioli","sequence":"additional","affiliation":[{"name":"University of Padova, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad","family":"Aliannejadi","sequence":"additional","affiliation":[{"name":"University of Amsterdam, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicola","family":"Ferro","sequence":"additional","affiliation":[{"name":"University of Padova, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Josiane","family":"Mothe","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Toulouse, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,10,10]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Future of information retrieval research in the age of generative AI. arXiv preprint arXiv:2412.02043","author":"Allan James","year":"2024","unstructured":"James Allan, Eunsol Choi, Daniel P Lopresti, and Hamed Zamani. 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Estimating the query difficulty for information retrieval. Synthesis Lectures on Information Concepts, Retrieval, and Services, 2(1):1\u201389, 2010."},{"key":"e_1_2_1_5_1","first-page":"28","volume-title":"Ian Soboroff. Sigir workshop report: Predicting query difficulty - methods and applications. In ACM SIGIR Forum","volume":"39","author":"Carmel David","unstructured":"David Carmel, Elad Yom-Tov, and Ian Soboroff. Sigir workshop report: Predicting query difficulty - methods and applications. In ACM SIGIR Forum, volume 39, pages 25\u201328. ACM New York, NY, USA, 2005."},{"key":"e_1_2_1_6_1","first-page":"204","volume-title":"ECIR","author":"Datta Suchana","year":"2024","unstructured":"Suchana Datta, Debasis Ganguly, Sean MacAvaney, and Derek Greene. A deep learning approach for selective relevance feedback. In ECIR, pages 189\u2013204, 2024."},{"issue":"1","key":"e_1_2_1_7_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3231937","article-title":"Learning to adaptively rank document retrieval system configurations","volume":"37","author":"Deveaud Romain","year":"2018","unstructured":"Romain Deveaud, Josiane Mothe, Md Zia Ullah, and Jian-Yun Nie. Learning to adaptively rank document retrieval system configurations. TOIS, 37(1):1\u201341, 2018.","journal-title":"TOIS"},{"key":"e_1_2_1_8_1","first-page":"58","volume-title":"ECIR","author":"Ebrahimi Sajad","year":"2024","unstructured":"Sajad Ebrahimi, Maryam Khodabakhsh, Negar Arabzadeh, and Ebrahim Bagheri. Estimating query performance through rich contextualized query representations. In ECIR, pages 49\u201358, 2024."},{"key":"e_1_2_1_9_1","first-page":"391","volume-title":"ECIR","author":"Faggioli Guglielmo","year":"2023","unstructured":"Guglielmo Faggioli, Nicola Ferro, Josiane Mothe, and Fiana Raiber. QPP++ 2023: Query-performance prediction and its evaluation in new tasks. In ECIR, pages 388\u2013391. Springer, 2023a."},{"key":"e_1_2_1_10_1","first-page":"7","volume-title":"Maik Fr\u00f6be. Report on the 1st workshop on query performance prediction and its evaluation in new tasks (QPP++ 2023) at ECIR 2023. In ACM SIGIR Forum","volume":"57","author":"Faggioli Guglielmo","year":"2023","unstructured":"Guglielmo Faggioli, Nicola Ferro, Josiane Mothe, Fiana Raiber, and Maik Fr\u00f6be. Report on the 1st workshop on query performance prediction and its evaluation in new tasks (QPP++ 2023) at ECIR 2023. In ACM SIGIR Forum, volume 57, pages 1\u20137, 2023b."},{"key":"e_1_2_1_11_1","first-page":"46","volume-title":"IIR","author":"Faggioli Guglielmo","year":"2023","unstructured":"Guglielmo Faggioli, Nicola Ferro, Cristina Muntean, Raffaele Perego, and Nicola Tonellotto. A spatial approach to predict performance of conversational search systems. In IIR, pages 41\u201346, 2023c."},{"key":"e_1_2_1_12_1","volume-title":"Raffaele Perego, and Nicola Tonellotto. A geometric framework for query performance prediction in conversational search. In SIGIR, page 1355\u20131365","author":"Faggioli Guglielmo","year":"2023","unstructured":"Guglielmo Faggioli, Nicola Ferro, Cristina Ioana Muntean, Raffaele Perego, and Nicola Tonellotto. A geometric framework for query performance prediction in conversational search. In SIGIR, page 1355\u20131365, 2023d."},{"key":"e_1_2_1_13_1","first-page":"2307","volume-title":"SIGIR","author":"Ganguly Debasis","year":"2023","unstructured":"Debasis Ganguly and Emine Yilmaz. Query-specific variable depth pooling via query performance prediction. In SIGIR, pages 2303\u20132307, 2023."},{"key":"e_1_2_1_14_1","first-page":"1317","volume-title":"SIGIR","author":"Khramtsova Ekaterina","year":"2024","unstructured":"Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, and Guido Zuccon. 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In SIGIR, pages 1089\u20131092, 2018."},{"key":"e_1_2_1_33_1","volume-title":"Agentic retrieval-augmented generation: A survey on agentic RAG. arXiv preprint arXiv:2501.09136","author":"Singh Aditi","year":"2025","unstructured":"Aditi Singh, Abul Ehtesham, Saket Kumar, and Tala Talaei Khoei. Agentic retrieval-augmented generation: A survey on agentic RAG. arXiv preprint arXiv:2501.09136, 2025."},{"key":"e_1_2_1_34_1","first-page":"14937","volume-title":"EMNLP","author":"Sun Weiwei","year":"2023","unstructured":"Weiwei Sun, Lingyong Yan, Xinyu Ma, Shuaiqiang Wang, Pengjie Ren, Zhumin Chen, Dawei Yin, and Zhaochun Ren. Is ChatGPT good at search? investigating large language models as re-ranking agents. In EMNLP, pages 14918\u201314937, 2023."},{"key":"e_1_2_1_35_1","first-page":"4","volume-title":"ADCS","author":"Thomas Paul","year":"2017","unstructured":"Paul Thomas, Falk Scholer, Peter Bailey, and Alistair Moffat. Tasks, queries, and rankers in pre-retrieval performance prediction. 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