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README.md

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 # Geneformer-CAB: Benchmarking Scale and Architecture in Foundation Models for Single-Cell Transcriptomics
 - Model Overview:
 
-Geneformer-CAB (Cumulative-Assignment-Blocking) is a benchmarked variant of the Geneformer architecture for modeling single-cell transcriptomic data.
-Rather than introducing an entirely new model, Geneformer-CAB systematically evaluates how data scale and architectural refinements interact to influence model generalization, predictive diversity, and robustness to batch effects.
+Geneformer-CAB (Cumulative-Assignment-Blocking, GF-CAB) is a benchmarked variant of the Geneformer architecture for modeling single-cell transcriptomic data.
+Rather than introducing an entirely new model, GF-CAB systematically evaluates how data scale and architectural refinements interact to influence model generalization, predictive diversity, and robustness to batch effects.
 
 - This model integrates two architectural enhancements:
 
@@ -28,4 +28,4 @@ Rather than introducing an entirely new model, Geneformer-CAB systematically eva
 
 2. Similarity-based regularization, which penalizes redundant token predictions to promote diversity and alignment with rank-ordered gene expression profiles.
 
-Together, these mechanisms provide insight into the limits of scale in single-cell foundation models — revealing that scaling up pretraining data does not always yield superior downstream performance.
+Together, these mechanisms provide insight into the limits of scale in single-cell foundation models, revealing that scaling up pretraining data does not always yield superior downstream performance.