@inproceedings{f148f4ba1ab74910bfe16d798eb8252a,
title = "PROTLLM: An Interleaved Protein-Language LLM with Protein-as-Word Pre-Training",
abstract = "We propose PROTLLM, a versatile cross-modal large language model (LLM) for both protein-centric and protein-language tasks. PROTLLM features a unique dynamic protein mounting mechanism, enabling it to handle complex inputs where the natural language text is interspersed with an arbitrary number of proteins. Besides, we propose the protein-as-word language modeling approach to train PROTLLM. By developing a specialized protein vocabulary, we equip the model with the capability to predict not just natural language but also proteins from a vast pool of candidates. Additionally, we construct a large-scale interleaved protein-text dataset, named InterPT, for pre-training. This dataset comprehensively encompasses both (1) structured data sources like protein annotations and (2) unstructured data sources like biological research papers, thereby endowing PROTLLM with crucial knowledge for understanding proteins. We evaluate PROTLLM on classic supervised protein-centric tasks and explore its novel protein-language applications. Experimental results demonstrate that PROTLLM not only achieves superior performance against protein-specialized baselines on protein-centric tasks but also induces zero-shot and in-context learning capabilities on protein-language tasks.",
author = "Le Zhuo and Zewen Chi and Minghao Xu and Heyan Huang and Jianan Zhao and Heqi Zheng and Conghui He and Mao, {Xian Ling} and Wentao Zhang",
note = "Publisher Copyright: {\textcopyright} 2024 Association for Computational Linguistics.; 62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024 ; Conference date: 11-08-2024 Through 16-08-2024",
year = "2024",
doi = "10.18653/v1/2024.acl-long.484",
language = "English",
series = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",
publisher = "Association for Computational Linguistics (ACL)",
pages = "8950--8963",
editor = "Lun-Wei Ku and Martins, {Andre F. T.} and Vivek Srikumar",
booktitle = "Long Papers",
address = "United States",
}