AINeutralarXiv – CS AI · Mar 64/10
🧠
A unified foundational framework for knowledge injection and evaluation of Large Language Models in Combustion Science
Researchers developed the first comprehensive framework for creating domain-specialized Large Language Models for combustion science, using 3.5 billion tokens from scientific literature and code. The study found that standard RAG approaches hit a performance ceiling at 60% accuracy, highlighting the need for more advanced knowledge injection methods including knowledge graphs and continued pretraining.