Dataset Groups Activity Stream Self-StrAE at SemEval-2024 Task 1: Making Self-Structuring AutoEncoders Learn More With Less Self-StrAE is a model that processes a given sentence to generate both multi-level embeddings and a structure over the input. BibTex: @dataset{Mattia_Opper_and_N_Siddharth_2024, abstract = {Self-StrAE is a model that processes a given sentence to generate both multi-level embeddings and a structure over the input.}, author = {Mattia Opper and N. Siddharth}, doi = {10.57702/ld7gxo41}, institution = {No Organization}, keyword = {'Natural Language Processing', 'Self-StrAE', 'Semantic Textual Similarity'}, month = {dec}, publisher = {TIB}, title = {Self-StrAE at SemEval-2024 Task 1: Making Self-Structuring AutoEncoders Learn More With Less}, url = {https://service.tib.eu/ldmservice/dataset/self-strae-at-semeval-2024-task-1--making-self-structuring-autoencoders-learn-more-with-less}, year = {2024} }
