Rethinking Class Imbalance for Single-Cell Foundation Models: A Systematic Benchmark Across Architectures and Long-Tail Loss Functions

arXiv:2609.23325 · cs.LG · Submitted 2026-09-20 · Read on arXiv

cs.LG

Submitted: 2026-09-20

Updated: 2026-09-20

Code: https://github.com/jz890/scimbalance

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Foundation Model — 23× in this paper · explained in 3 episodes
• Foundation Models — 20× in this paper · explained in 7 episodes
• Benchmark — 19× in this paper · explained in 2 episodes
• Accuracy — 15× in this paper · explained in 1 episode
• Loss Function — 11× in this paper · explained in 2 episodes
• Embeddings — 5× in this paper · explained in 2 episodes
• Calibration — 4× in this paper · explained in 7 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Benchmarking — 3× in this paper · explained in 4 episodes
• Contrastive Learning — 3× in this paper · explained in 5 episodes
• Decoupling — 3× in this paper · explained in 2 episodes
• F1 Score — 3× in this paper · explained in 3 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Linear probe — 2× in this paper · explained in 2 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Tokenization — 2× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Linear Probing — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• A Survey of Deep Long-Tail Classification Advancements
• Prototype Guided Post-pretraining for Single-Cell Representation Learning
• Celler:A Genomic Language Model for Long-Tailed Single-Cell Annotation

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