Domain Adapted Large Language Models for Additive Manufacturing
Researchers have developed specialized large language models for additive manufacturing by adapting open-weight models like Gemma 3, Qwen 3, and Gemma 4. These models were trained on approximately 50 million tokens of additive manufacturing journal articles, incorporating both text and visual data. Evaluations using the Additive-Manufacturing-Benchmark show these domain-adapted models achieve over 90% accuracy on additive manufacturing knowledge tasks, demonstrating an effective method for LLM specialization. AI
IMPACT Demonstrates a viable method for specializing LLMs for niche industrial applications, potentially improving efficiency and knowledge access in fields like additive manufacturing.