ArticleChemical science2024
nach0: multimodal natural and chemical languages foundation model.
Article in Chemical science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Fine-Tuning DeepSeek-OCR‑2 for Molecular Structure Recognition.ACS omega · 2026Article
- Chemical language models for early-stage drug discovery: applications, pitfalls, and future directions.Journal of computer-aided molecular design · 2026Review
- Organic Chemistry as a Catalyst for AI Innovation: Challenges, Methods, and Emerging Paradigms.Chemical reviews · 2026Review
- A survey on large language models in biology and chemistry.Experimental & molecular medicine · 2026Review
- General-Purpose Models for the Chemical Sciences: LLMs and Beyond.Chemical reviews · 2026Review
- Multimodal pre-training models of molecular representation for drug discovery.National science review · 2026Review
- Application and Prospects of Large Language Models in Small-Molecule Drug Discovery.Analytical chemistry · 2025Review
- Measuring Chemical LLM robustness to molecular representations: a SMILES variation-based framework.Journal of cheminformatics · 2025Article
- AI and automation: democratizing automation and the evolution towards true AI-autonomous robotics.Chemical science · 2025Review
- Chemical Language Model Linker: Blending Text and Molecules with Modular Adapters.Journal of chemical information and modeling · 2025Article
- Article
- Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry.Chemical Society reviews · 2025Review
- RPSubAlign: a novel sequence-based molecular representation method for retrosynthesis prediction with improved validity and robustness.Briefings in bioinformatics · 2025Article
- Unified Deep Learning of Molecular and Protein Language Representations with T5ProtChem.Journal of chemical information and modeling · 2025Article
- A Perspective on Foundation Models in Chemistry.JACS Au · 2025Review
- Revolutionizing oncology: the role of Artificial Intelligence (AI) as an antibody design, and optimization tools.Biomarker research · 2025Review
- A review of large language models and autonomous agents in chemistry.Chemical science · 2025Review
- An automatic end-to-end chemical synthesis development platform powered by large language models.Nature communications · 2024Article
- Machine learning predicts upper secondary education dropout as early as the end of primary school.Scientific reports · 2024Article
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Authors and funding
11 authors.
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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 to incorporate a range of chemical and linguistic knowledge. We employed instruction tuning, where specific task-related instructions are utilized to fine-tune nach0 for the final set of tasks. To train nach0 effectively, we leverage the NeMo framework, enabling efficient parallel optimization of both base and large model versions. Extensive experiments demonstrate that our model outperforms state-of-the-art baselines on single-domain and cross-domain tasks. Furthermore, it can generate high-quality outputs in molecular and textual formats, showcasing its effectiveness in multi-domain setups.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.