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welcome to my presentation on training state-of-the-art text embedding and new search models at the milan nlp group check out their work on contextualized topic models itamp;#39;s a really nice application of dense embedding models iamp;#39;m niels i work as research scientist walking face and iamp;#39;m the maintainer of sentence transformers in this talk i was first give a short introduction on why why are dense vector spaces and representation interesting then i will talk um how to train this mode especially i will go into a lot of detail how to train state-of-the-art models and what are the tricks to get really good models then i will give a short overview over multilingual models i will present different more search architectures besides these models and then i will talk about serious short information retrieval benchmarking so why dense representations for text so traditionally we use the text a sparse lexical representation also known as back of words so each word has its own
