11 citations · 29 across the 5 of their papers we have counts for
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cs.CV2022★ 6 cited
Weakly supervised training of universal visual concepts for multi-domain semantic segmentation
Petra Bevandić, Marin Oršić, Ivan Grubišić +2
Deep supervised models have an unprecedented capacity to absorb large quantities of training data. Hence, training on multiple datasets becomes a method of choice towards strong ge…
cs.CL2022★ 1 cited
IRB-NLP at SemEval-2022 Task 1: Exploring the Relationship Between Words and Their Semantic Representations
Damir Korenčić, Ivan Grubišić
What is the relation between a word and its description, or a word and its embedding? Both descriptions and embeddings are semantic representations of words. But, what information…