May 1, 2024, 4:43 a.m. | Micha Livne, Zulfat Miftahutdinov, Elena Tutubalina, Maksim Kuznetsov, Daniil Polykovskiy, Annika Brundyn, Aastha Jhunjhunwala, Anthony Costa, Alex Al

cs.LG updates on arXiv.org arxiv.org

arXiv:2311.12410v2 Announce Type: replace-cross
Abstract: Large Language Models (LLMs) have substantially driven scientific progress in various domains, and many papers have demonstrated their ability to tackle complex problems with creative solutions. Our paper introduces a new foundation model, nach0, capable of solving various chemical and biological tasks: biomedical question answering, named entity recognition, molecular generation, molecular synthesis, attributes prediction, and others. nach0 is a multi-domain and multi-task encoder-decoder LLM pre-trained on unlabeled text from scientific literature, patents, and molecule strings …

abstract arxiv biomedical creative cs.ai cs.cl cs.lg domains foundation foundation model language language models languages large language large language models llms multimodal natural paper papers progress q-bio.qm question question answering scientific solutions tasks type

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