Scaling Generative Retrieval: Google Research and University of Waterloo’s Empirical Study on Generative Retrieval Across Diverse Corpus Scales, Including a Deep Dive into the 8.8M-Passage MS MARCO Task

In a revolutionary leap forward, generative retrieval approaches have emerged as a disruptive paradigm in information retrieval methods. Harnessing the potential of advanced sequence-to-sequence Transformer models, these approaches aim to transform how we retrieve information from vast document corpora. Traditionally limited to smaller datasets, a recent groundbreaking study titled “How Does Generative Retrieval Scale to […]

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