Our paper, “Equi-mRNA: Protein Translation Equivariant Encoding for mRNA Language Models,” has been accepted to NeurIPS 2025. We present a codon-level equivariant architecture that models synonymous codon symmetries through group-theoretic priors, achieving up to 10% higher accuracy and more biologically realistic mRNA generation that better preserves functional properties.