Program
This listing is based on OpenReview data extracted at the time the acceptance notifications were sent out. If you see errors in spelling or capitalization and so on, make sure that you correct them when you are completing the ACM Rights Review Form via the link you will receive shortly.
When checking the ACM Rights Review Form you should verify the author names and affiliations very carefully. in every respect. As well, please ensure that all authors from the same institution have a consistent form of the institution's name. For example, all of "The University of Nowhere" and "University of Nowhere" and "Nowhere University" might be fine separately, but please don't have a mixture of them on the same paper.
The final version of your paper must then have exactly the same author names and affiliations, identical in every detail to the submitted Rights Review Form. Even very minor inconsistencies are likely to be queried by the ACM; and mismatches that are not rectified promptly risk delaying publication of the proceedings (maybe you don't care) or risk your paper being excluded from the proceedings (maybe you do care!).
Note that we will not be applying name/title corrections requested through the ACM Rights Review process to this preliminary acceptance listing. This page is a static snapshot of the paper titles and authors names used to initiate the ACM Rights Review process, and will not get edited further. A detailed program with corrected title and author names will be prepared once all camera-ready versions have been received by the ACM and approved, and once the papers have been assigned to sessions.
And as a reminder: camera-ready versions must be uploaded by 14 June (AoE); and registration of a presenting author is required by 14 June (Melbourne time), see https://sigir2026.org/en-AU/pages/attending/registration.
Please pay careful attention to the information about page lengths, required information, and ACM Author Page Charges that was provided in the acceptance emails.
All papers will be presented as posters, A0 portrait format.
In addition, a selection of papers will be invited for oral presentation, with that selection made on the basis of likely interest to the anticipated audience and to span a variety of topics, and not as a measure of paper importance. All accepted papers rank equally in terms of importance, regardless of length or presentation format. The decision on the presentation format of each accepted paper will be sent by email within two weeks.
A set of 44 papers have been accepted for ICTIR 2026.
Exposure-Based Reinforcement Learning to Rank
Harrie Oosterhuis, Rolf Jagerman, Zhen Qin, Xuanhui Wang
RoTRAG: Rule of Thumb Reasoning for Conversation Harm Detection with Retrieval-Augmented Generation
Juhyeon Lee, Wonduk Seo, Junseo Koh, Seunghyun lee, Haihua Chen, Yi Bu
Model Merging as an Alternative to Fine-Tuning on Combined Data for a Multi-Domain Dense Retriever
Taiga Sasaki, Takehiro Yamamoto, Hiroaki Ohshima, Sumio Fujita
RAMP: Robust Ad Recommendation Under Limited Personalized-Feature Availability via Masking and Alignment Pathways
Dairui Liu, Zhongyi Lu, Roger Zhe Li, Changhong Jin, Jitao Lu, Xinyang Shao, Bichen Shi, Mete Sertkan, Aghiles Salah, Aonghus Lawlor, Barry Smyth, Tri Kurniawan Wijaya, Ruihai Dong, Xingsheng Guo
Adaptive Token-Aware Query Reformulation for Text-to-Image Retrieval
Seonah Kim, MinKeon Kim, Youjin Lee, Jaekwang Kim, Jinyoung Han, Eunil Park
ARIC: A Cognitive Framework for Explanatory Narrative Evaluation in Conversational Information Seeking Systems
Vahid Sadiri Javadi, Sadia Naseer, Ali Ather, Lucie Flek, Johanne Trippas
As We May Search
Saber Zerhoudi, Adam Roegiest, Jelena Mitrović, Michael Granitzer
Reasoning with Large Language Models for Relevance Judgements
Louis Geiger, Danula Hettiachchi, Falk Scholer, Johanne Trippas
Bridging the Gap between Subsampled and Full-Corpus Evaluation
Michael Dinzinger, Kanishka Ghosh Dastidar, Laura Caspari, Jelena Mitrović, Michael Granitzer
Relaxed Term Matching for Neural Axiomatic Diagnostics
Andrew Parry, Maik Fröbe, Martin Potthast, Sean MacAvaney, Benno Stein, Matthias Hagen, Debasis Ganguly
Interpretable Legal Similarity: From Embeddings to Obligations
Adam Roegiest, Johanne Trippas
Ranking Passages in Relevant Documents Using LLMs
Eyal El Ani, Eilon Sheetrit, Oren Kurland
A Design Science Framework for Human-Agent Teams in Information Retrieval
Chirag Shah, Lynda Tamine, Mouly Dewan
DeepResearchGym: A Free, Transparent, and Reproducible Sandbox for Deep Research
João Coelho, Jingjie Ning, Jingyuan He, Kangrui Mao, Abhijay Sai Paladugu, Pranav Setlur, Jiahe Jin, Jamie Callan, Joao Magalhaes, Bruno Martins, Chenyan Xiong
Does Form Affect Function? An Extended Study of LLM Re-Ranking Behavior
Reyhaneh Goli, Alistair Moffat
Entity Labels Are Not Entity Signals: A Framework for Observable Relevance in Document Re-Ranking
Utshab Kumar Ghosh, Shubham Chatterjee
Proposing an Evaluation Framework for Legal Case Retrieval Beyond Binary Relevance: A Bibliographic Coupling Approach
Atsuhito Sekiguchi, Masaharu Yoshioka, Calum Kwan
Equity by Design? On the Trade-Offs in Fairness-Driven Recommendation in Heterogeneous Two-Sided Markets
Dominykas Seputis, Rajeev Verma, Alexander Timans
Rank, Don't Generate: Statement-level Ranking for Explainable Recommendation
Ben Kabongo, Arthur Satouf, Vincent Guigue
Plan-and-Refine in RAG: Generating Diverse and Comprehensive Responses through Global Exploration and Local Exploitation
Alireza Salemi, Chris Samarinas, Hamed Zamani
Preventing Content Leakage in LLM-Based Medical RAG: Structure-Only Retrieval for Faithful Clinical Summarization
Aleka Melese Ayalew, Tapio Seppänen, Mourad Oussalah
Stability in Competitive Search with Results Diversification
Itamar Reinman, Omer Madmon, Moshe Tennenholtz, Oren Kurland
Search Arena Meets Nuggets: Towards Explanations and Diagnostics in the Evaluation of LLM Responses
Sahel Sharifymoghaddam, Shivani Upadhyay, Nandan Thakur, Ronak Pradeep, Jimmy Lin
Prior-Data Fitted Networks as Tabular Foundation Models for Ranking in Low-Data Settings
David Vos, Samarth Bhargav, Maarten de Rijke, Harrie Oosterhuis
Rank-ICL: Ranking-based In-context Learning for Search Result Explanation
Arif Laksito, Aali Alqarni, Mark Stevenson
A Theoretical Framework for Risk Analysis of Stochastic Rankers
Debasis Ganguly
RAAD: Retrieval-Augmented Ambiguity Detection via Answer Diversity
Parth Patel, Sarah Kamoun, Bita Azad, Faezeh Ensan
A Replicability Study of XTR
Rohan Jha
Beyond Relevance: On the Relationship Between Retrieval and RAG Information Coverage
Saron Samuel, Alexander Martin, Eugene Yang, Andrew Yates, Dawn Lawrie, Ian Soboroff, Laura Dietz, Benjamin Van Durme
DOGMATIQ: Automated Generation of Question-and-Answer Nuggets for Report Evaluation
Bryan Li, William Gantt Walden, Yu Hou, Gabrielle Kaili-May Liu, Chris Callison-Burch, Dawn Lawrie, James Mayfield, Eugene Yang, Laura Dietz
A comprehensive Taxonomy of Temporal Dimensions in Natural Language Queries
Ivano Lauriola
TopicTune: A Topic Alignment Approach to Improve LLMs Reasoning on Social Questions
Maryam Amirizaniani, Baktash Ansari, Chirag Shah, Afra Mashhadi
RIDRec: Retrieval-Enhanced Intent Diffusion for Anonymous Short-Session Recommendation
Peilin Liu, Zhiquan Ji, Gang Yan
LLM-Driven Usefulness Judgment for Web Search Evaluation
Mouly Dewan, Jiqun Liu, Aditya Gautam, Chirag Shah
To Believe or Not To Believe: Comparing Supporting Information Tools to Aid Human Judgments of AI Veracity
Jessica Irons, Patrick Cooper, Necva Bölücü, Andreas Duenser, Roelien C. Timmer, Huichen Yang, Changhyun Lee, Brian Jin, Stephen Wan
Uncertainty Quantification for Multimodal Retrieval Augmented Generation
Simon Binz, Heydar Soudani, Faegheh Hasibi
Towards Adaptive and Retriever-friendly Retrieval-augmented Generation via Reinforcement Learning
Yubo Fang, Hai-Tao Yu, Hideo Joho, Sumio Fujita
Analysis of Reasoning-Intensive Retrieval in Japanese
Hiroki Kurokawa, Hirotaka Kameko, Shinsuke Mori
Sparse Retrieval is almost All You Need for Automated Fact-Checking
Ritvik Setty, Vinay Setty
MedQueryIntent: A Large-Scale Benchmark Dataset for Medical Search Intent Classification
Samantha Schnell, Supriya Kottam, Yingcheng Sun
Adaptive Re-Ranking
Ata Cinar Genc, Emir Kaan Korukluoglu, James Allan
From Noise to Order: Learning to Rank via Denoising Diffusion
Sajad Ebrahimi, Bhaskar Mitra, Negar Arabzadeh, Ye Yuan, Haolun Wu, Fattane Zarrinkalam, Ebrahim Bagheri
RecQuest: Towards Estimating User Domain Knowledge in Conversational Recommender Systems
Ivica Kostric, Ujwal Gadiraju, Krisztian Balog
Patent Representation Learning via Self-supervision
You Zuo, Kim Gerdes, Éric Villemonte de la Clergerie, Benoît Sagot