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：生成式信息检索已在多个研究领域（如信息检索、计算机视觉、自然语言处理及机器学习）取得显著进展，并在大众媒体中备受关注。当前已发布的理论研究、实证成果及面向用户的实际产品，可通过（生成式方法）检索文档，或基于输入请求直接生成答案。我们旨在探究端到端生成模型是短暂的潮流，还是如部分学者所言，标志着信息检索领域的范式变革。这需要新的评估指标、理论基础、评价方法、任务定义、模型架构及用户界面等。本研讨会（https://coda.io/@sigir/gen-ir）旨在聚焦已有探索的生成式IR技术（如文档检索与直接式基于事实的答案生成），同时为探讨生成式IR在推荐系统、文本摘要等新兴领域的应用提供平台。研讨会采用互动形式，包含圆桌讨论与主题演讲环节，避免传统小型会议的单向对话模式。