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Large language models have made significant strides in natural language processing, enabling innovative applications in molecular science by processing textual representations of molecules.
Scibert: A pretrained language model for scientific text
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An image is worth 16x16 words: Transformers for image recognition at scale
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Moleculenet: a benchmark for molecular machine learning
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Language models are unsupervised multitask learners
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An open source chemical structure curation pipeline using rdkit
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Gpt-3: Its nature, scope, limits, and consequences
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Text2mol: Cross-modal molecule retrieval with natural language queries, in: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp. 595–607
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Scaling up visual and vision-language representation learning with noisy text supervision, in: International Conference on Machine Learning, PMLR. pp. 4904–4916
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Decimer 1.0: deep learning for chemical image recognition using transformers
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Flamingo: a visual language model for few-shot learning
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Vlmo: Unified vision-language pre-training with mixture-of-modality-experts
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Generative models for molecular discovery: Recent advances and challenges
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Translation between molecules and natural language, in: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pp. 375–413
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Graphmae: Self-supervised masked graph autoencoders, in: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 594–604
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Multi-modal molecule structure-text model for text-based retrieval and editing
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Diffusion models: A comprehensive survey of methods and applications
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A deep-learning system bridging molecule structure and biomedical text with comprehension comparable to human professionals
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One transformer fits all distributions in multi-modal diffusion at scale
Bao, F., Nie, S., Xue, K., Li, C., Pu, S., Wang, Y., Yue, G., Cao, Y., Su, H., Zhu, J., 2023 · 2023
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Language is not all you need: Aligning perception with language models
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Druggpt: A gpt-based strategy for designing potential ligands targeting specific proteins
Li, Y., Gao, C., Song, X., Wang, X., Xu, Y., Han, S., 2023c · 2023
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Visual chatgpt: Talking, drawing and editing with visual foundation models
Wu, C., Yin, S., Qi, W., Wang, X., Tang, Z., Duan, N., 2023 · 2023
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Uni-mol: A universal 3d molecular representation learning framework, in: The Eleventh International Conference on Learning Representations
Zhou, G., Gao, Z., Ding, Q., Zheng, H., Xu, H., Wei, Z., Zhang, L., Ke, G., 2023 · 2023
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Minigpt-4: Enhancing vision-language understanding with advanced large language models
Zhu, D., Chen, J., Shen, X., Li, X., Elhoseiny, M., 2023 · 2023
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