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cs.CL2024
Learning to Plan for Language Modeling from Unlabeled Data
Nathan Cornille, Marie-Francine Moens, Florian Mai
By training to predict the next token in an unlabeled corpus, large language models learn to perform many tasks without any labeled data. However, their next-token-prediction objec…
cs.CL2024
Triple-Encoders: Representations That Fire Together, Wire Together
Justus-Jonas Erker, Florian Mai, Nils Reimers +2
Search-based dialog models typically re-encode the dialog history at every turn, incurring high cost. Curved Contrastive Learning, a representation learning method that encodes rel…