Generative information retrieval (IR) has experienced substantial growth across multiple research communities (e.g., information retrieval, computer vision, natural language processing, and machine learning), and has been highly visible in the popular press. Theoretical, empirical, and actual user-facing products have been released that retrieve documents (via generation) or directly generate answers given an input request. We would like to investigate whether end-to-end generative models are just another trend or, as some claim, a paradigm change for IR. This necessitates new metrics, theoretical grounding, evaluation methods, task definitions, models, user interfaces, etc. The goal of this workshop (https://coda.io/@sigir/gen-ir) is to focus on previously explored Generative IR techniques like document retrieval and direct Grounded Answer Generation, while also offering a venue for the discussion and exploration of how Generative IR can be applied to new domains like recommendation systems, summarization, etc. The format of the workshop is interactive, including roundtable and keynote sessions and tends to avoid the one-sided dialogue of a mini-conference.

翻译：生成式信息检索在多个研究领域（如信息检索、计算机视觉、自然语言处理和机器学习）经历了显著增长，并在大众媒体中备受关注。目前已发布的理论、实证及面向用户的实际产品，可通过生成方式检索文档，或根据输入请求直接生成答案。我们试图探究：端到端生成模型是又一波潮流，还是如某些人所言，代表了信息检索领域的范式变革？这需要新的指标、理论基础、评估方法、任务定义、模型、用户界面等。本研讨会（https://coda.io/@sigir/gen-ir）旨在聚焦此前已探索的生成式信息检索技术（如文档检索与直接有依据答案生成），同时为讨论和探索如何将生成式信息检索应用于推荐系统、摘要等新领域提供平台。研讨会形式注重互动性，包含圆桌讨论与主旨发言环节，力求避免微型会议式的单向对话。