AdditiveLLM2: A Multi-modal Large Language Model for Additive Manufacturing
This work presents AdditiveLLM2 a multi-modal, domain adapted large language model built upon the instruction tuned variant of the Gemma 3 model using a relatively small dataset of around 50 million tokens. The dataset (AdditiveLLM2-OA) consists of open-access additive manufacturing journal articles with data extracted for the domain adaptive pretraining and visual instruction tuning processes. Various stages of the developed model are evaluated with the Additive-Manufacturing-Benchmark which consists of additive manufacturing domain specific tasks compiled published resources. AdditiveLLM2 exhibits proficiency in both language and vision based tasks, achieving accuracies upwards of 90% in general additive manufacturing knowledge. This domain adaptive pretraining and instruction tuning strategy outline an accessible specialization method for large language models to a domain such as additive manufacturing.
69c2acd295b48f16a3007613
Peter Pak
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2026-03-25T10:51:10.711Z
62acaad9dc7f5a3905140c64
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Peter Pak
ppak10
user
ppak10
69c2acd295b48f16a3007614
Amir Barati Farimani
AdditiveLLM2: A Multi-modal Large Language Model for Additive Manufacturing
This work presents AdditiveLLM2 a multi-modal, domain adapted large language model built upon the instruction tuned variant of the Gemma 3 model using a relatively small dataset of around 50 million tokens. The dataset (AdditiveLLM2-OA) consists of open-access additive manufacturing journal articles with data extracted for the domain adaptive pretraining and visual instruction tuning processes. Various stages of the developed model are evaluated with the Additive-Manufacturing-Benchmark which consists of additive manufacturing domain specific tasks compiled published resources. AdditiveLLM2 exhibits proficiency in both language and vision based tasks, achieving accuracies upwards of 90% in general additive manufacturing knowledge. This domain adaptive pretraining and instruction tuning strategy outline an accessible specialization method for large language models to a domain such as additive manufacturing.
AdditiveLLM2 demonstrates high accuracy in additive manufacturing tasks through domain-adaptive pretraining and instruction tuning of a Gemma 3-based model.
multi-modal domain adaptation large language model instruction tuning Gemma 3 additive manufacturing domain-specific benchmark visual instruction tuning domain-adaptive pretraining