ACM Digital Library <https://maestro.acm.org/trk/click?ref=z16l2snue3_2-31603_0x332a2ax019610> [image: journal banner] <https://maestro.acm.org/trk/click?ref=z16l2snue3_2-31603_0x33ae5dx019610> *CALL FOR PAPERS*
*ACM Transactions on Information Systems* *Special Issue on Query Performance Prediction Towards Novel Information Retrieval Paradigms* *Guest Editors* Dr. Suchana Datta <https://maestro.acm.org/trk/click?ref=z16l2snue3_2-31603_0x341ef9x019610>, University College Dublin, Ireland Dr. Guglielmo Faggioli <https://maestro.acm.org/trk/click?ref=z16l2snue3_2-31603_0x341efax019610>, University of Padua, Italy Prof. Nicola Ferro <https://maestro.acm.org/trk/click?ref=z16l2snue3_2-31603_0x341efbx019610>, University of Padua, Italy Dr. Debasis Ganguly <https://maestro.acm.org/trk/click?ref=z16l2snue3_2-31603_0x341efcx019610>, University of Glasgow, United Kingdom Prof. Iadh Ounis <https://maestro.acm.org/trk/click?ref=z16l2snue3_2-31603_0x341efdx019610>, University of Glasgow, United Kingdom [image: journal cover image]This special issue focuses on works involving QPP models that employ or are designed for novel searching and filtering paradigms, including but not limited to neural IR, Large Language Models, and Retrieval Augmented Generation, as well as the QPP evaluation paradigms also in light of recent IR advances. QPP is a branch of IR evaluation: it is defined as the task of assessing or predicting the performance of a query without human-made relevance judgements. The focus of the special issue will be on three major topics concerning QPP: • The development of novel QPP models that employ recent neural state-of-the-art solutions, such as Large Language Models (LLMs) and semantic representations. • The application of QPP models to novel IR tasks, such as conversational search, fairness-oriented tasks, multimedia and multimodal retrieval, and Retrieval Augmented Generation (RAG). • The evaluation of QPP methods performance. *Topics*We welcome submissions on the following topics, including but not limited to: • Application of QPP to Neural Information Retrieval Systems • Usage of QPP for modern tasks, including, but not limited to, conversational search, fairness, RAG, multimodal retrieval • Usage of Large Language Models for QPP • QPPs based on non-lexical (e.g., semantic, multimodal) signals • Supervised QPP • Simulation and construction of evaluation collections with Large Language Models • QPP evaluation measures • Development of QPP evaluation collection • Performance Prediction in neighboring areas including NLP and Recommender Systems • Theory underneath QPP • Applications of QPP for downstream tasks, e.g., selective application of second-stage ranking or relevance feedback. • Explainability of QPP models and QPP models for explainability *Click here for the full Call for Papers and submission instructions.* <https://maestro.acm.org/trk/click?ref=z16l2snue3_2-31603_0x341efex019610> *Important Dates* Submissions deadline: March 15, 2025 First-round review decisions: May 15, 2025 Deadline for revision submissions: July 15, 2025 Notification of final decisions: September 15, 2025 Tentative publication: Late 2025 For questions and further information, please write to *Dr. Guglielmo Faggioli* at [email protected] <https://maestro.acm.org/trk/click?ref=z16l2snue3_2-31603_0x341effx019610>. Sign up for TOIS TOC alerts. <https://maestro.acm.org/trk/click?ref=z16l2snue3_2-31603_0x341f00x019610> *https://tois.acm.org* <https://maestro.acm.org/trk/click?ref=z16l2snue3_2-31603_0x341f01x019610>
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