Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
Conference on Empirical Methods in Natural Language Processing (EMNLP)
Many of the world’s languages employ grammatical gender on the lexeme. For example, in Spanish, the word for house (casa) is feminine, whereas the word for paper (papel) is masculine. To a speaker of a genderless language, this assignment seems to exist with neither rhyme nor reason. But is the assignment of inanimate nouns to grammatical genders truly arbitrary? We present the first large-scale investigation of the arbitrariness of noun–gender assignments. To that end, we use canonical correlation analysis to correlate the grammatical gender of inanimate nouns with an externally grounded definition of their lexical semantics. We find that 18 languages exhibit a significant correlation between grammatical gender and lexical semantics.
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
Bilge Acun, Benjamin Lee, Fiodar Kazhamiaka, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu
Harjasleen Malvai, Lefteris Kokoris-Kogias, Alberto Sonnino, Esha Ghosh, Ercan Ozturk, Kevin Lewi, Sean Lawlor