nach0: multimodal natural and chemical languages foundation model

Livne, Micha; Miftahutdinov, Zulfat; Tutubalina, Elena; Kuznetsov, Maksim; Polykovskiy, Daniil; Brundyn, Annika; Jhunjhunwala, Aastha; Costa, Anthony; Aliper, Alex; Aspuru-Guzik, Alán; Zhavoronkov, Alex

doi:10.1039/d4sc00966e

Chem. Sci.

2024

DOI: 10.1039/d4sc00966e

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nach0: multimodal natural and chemical languages foundation model

Micha Livne,

Zulfat Miftahutdinov,

Elena Tutubalina

et al.

Abstract: nach0 is a novel multi-domain and multi-task language model pre-trained on unlabeled text from scientific literature, patents, and molecule strings to incorporate a range of chemical and linguistic knowledge.

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Machine learning predicts upper secondary education dropout as early as the end of primary school

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Education plays a pivotal role in alleviating poverty, driving economic growth, and empowering individuals, thereby significantly influencing societal and personal development. However, the persistent issue of school dropout poses a significant challenge, with its effects extending beyond the individual. While previous research has employed machine learning for dropout classification, these studies often suffer from a short-term focus, relying on data collected only a few years into the study period. This study expanded the modeling horizon by utilizing a 13-year longitudinal dataset, encompassing data from kindergarten to Grade 9. Our methodology incorporated a comprehensive range of parameters, including students’ academic and cognitive skills, motivation, behavior, well-being, and officially recorded dropout data. The machine learning models developed in this study demonstrated notable classification ability, achieving a mean area under the curve (AUC) of 0.61 with data up to Grade 6 and an improved AUC of 0.65 with data up to Grade 9. Further data collection and independent correlational and causal analyses are crucial. In future iterations, such models may have the potential to proactively support educators’ processes and existing protocols for identifying at-risk students, thereby potentially aiding in the reinvention of student retention and success strategies and ultimately contributing to improved educational outcomes.

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nach0: multimodal natural and chemical languages foundation model

Abstract: nach0 is a novel multi-domain and multi-task language model pre-trained on unlabeled text from scientific literature, patents, and molecule strings to incorporate a range of chemical and linguistic knowledge.

Cited by 3 publications

References 46 publications

Adversarial attacks and defenses for large language models (LLMs): methods, frameworks & challenges

Adversarial attacks and defenses for large language models (LLMs): methods, frameworks & challenges

Generative AI and process systems engineering: The next frontier

Machine learning predicts upper secondary education dropout as early as the end of primary school

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