Comparative Benchmarking of Probabilistic, Recurrent, and Self-Attention Models for Autoregressive Genomic Sequence Modeling
This work provides a resource-efficiency analysis and empirical benchmark for model selection in constrained genomic modeling tasks, highlighting that computationally expensive deep learning architectures do not unconditionally outperform lightweight statistical baselines on small, vocabulary-constrained genomic datase...