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cs.CL2024
End-to-end Planner Training for Language Modeling
Nathan Cornille, Florian Mai, Jingyuan Sun +1
Through end-to-end training to predict the next token, LLMs have become valuable tools for various tasks. Enhancing their core training in language modeling can improve numerous do…
cs.CL2024
Learning to Plan Long-Term for Language Modeling
Florian Mai, Nathan Cornille, Marie-Francine Moens
Modern language models predict the next token in the sequence by considering the past text through a powerful function such as attention. However, language models have no explicit…
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…