Generative Information Retrieval
Gen-IR
Find information in a corpus of documents (the web, wikipedia, movies, medical records, ...) given a particular query, in a generative way. “generative” can be understood in lot of ways: including, but not limited to, some mentioned in the topics below. We tentatively define two main fields below, Generative Document Retrieval and Grounded Answer Generation Generative Document Retrieveal
GDR
Given a query, retrieve a ranked list of existing documents via an encoder-decoder architecture. Oftentimes this involves a custom/learned indexing strategy.
Grounded Answer Generation
GAR
Retrieve a human readable generated answer that matches a query; the answer can link to or refer to a document.
Pretrained (Large) Language Model
PLM
Language models that are trained in a conventional self-supervised manner with no particular downstream task (e.g. GPT, T5, BART)