Gupta et al. developed MatSciBERT, a materials domain-specific language model for text mining and information extraction. They argued that conventional language processing alone, such as encoded in the form of BERT models, may not yield optimal results when applied to materials science due to their lack of training in materials-specific notations and terminology. To address this challenge, the authors introduced a specific materials-aware language model they refer to as MatSciBERT. This model was trained on an extensive corpus of peer-reviewed materials science publications. The authors claimed that their model surpasses SciBERT, a large language model trained on a broader and less materials-specific scientific corpus, in three critical tasks, named entity recognition, relation classification, and abstract classification.