{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/llamo-large-language-model-based-molecular","title":"LLaMo: Large Language Model-based Molecular Graph Assistant","arxiv_id":"2411.00871","date":"2024-10-31","proceeding":null,"authors":["Jinyoung Park","Minseong Bae","Dohwan Ko","Hyunwoo J. Kim"],"abstract":"Large Language Models (LLMs) have demonstrated remarkable generalization and instruction-following capabilities with instruction tuning. The advancements in LLMs and instruction tuning have led to the development of Large Vision-Language Models (LVLMs). 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