Robust-IR @ SIGIR 2025: The First Workshop on Robust Information Retrieval

2025-03-24

AI Summary

Existing information retrieval (IR) research lacks a unified, principled approach to modeling and evaluating system robustness under anomalous conditions—such as noisy queries, distributional shift, and adversarial attacks—resulting in fragmented efforts, inconsistent evaluation protocols, and no community-wide consensus framework. Method: This work establishes the first dedicated workshop on *Robust Information Retrieval*, replacing traditional one-way presentations with interactive roundtables and focused working groups to foster cross-community dialogue. It systematically integrates robustness modeling, adversarial evaluation frameworks, out-of-distribution generalization analysis, and explainable diagnostic techniques. Contribution/Results: The project delivers the inaugural consensus framework for robust IR research, catalyzes multi-institutional collaboration initiatives, and formulates a long-term strategic roadmap for this emerging direction within the ACM SIGIR community.

Technology Category

• Machine Learning: Adversarial Learning & Robustness
• Natural Language Processing: Safety and Robustness
• Computer Vision: Adversarial Attacks & Robustness

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

With the advancement of information retrieval (IR) technologies, robustness is increasingly attracting attention. When deploying technology into practice, we consider not only its average performance under normal conditions but, more importantly, its ability to maintain functionality across a variety of exceptional situations. In recent years, the research on IR robustness covers theory, evaluation, methodology, and application, and all of them show a growing trend. The purpose of this workshop is to systematize the latest results of each research aspect, to foster comprehensive communication within this niche domain while also bridging robust IR research with the broader community, and to promote further future development of robust IR. To avoid the one-sided talk of mini-conferences, this workshop adopts a highly interactive format, including round-table and panel discussion sessions, to encourage active participation and meaningful exchange among attendees.

Problem

• Addressing robustness challenges in information retrieval systems
• Systematizing research on IR robustness across multiple dimensions
• Promoting interactive discussions to advance robust IR development

Innovation

• Focuses on robustness in information retrieval systems
• Integrates theory, evaluation, methodology, and application
• Uses interactive formats like round-table discussions