Author

Samir Char

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#artificial intelligence Preprint Sep 2026

Bigger Text Encoders Can Hurt CLIP Zero-Shot Performance

Contrastive Language-Image Pretraining (CLIP) is a building block of many machine learning applications. Scaling laws have guided resource allocation for large-scale training, yet prior work treats total CLIP model size as a single variable, without exploring how the capacity split between encoders impacts downstream p...

Samir Char, Carles Domingo-Enrich, Randall Balestriero · 0 citations

Open access Aug 2026

Protein language models and the long tail of functional diversity

It is found that many GigaRef singletons belong to a cluster under alternative parameter settings, suggesting that genomic and metagenomic datasets may require dataset-specific clustering configurations, and it is shown that singletons share mutual information with clustered sequences, making them learnable by PLMs and...

R. Vinod, Samir Char, Ava A. Amini et al. · bioRxiv · 0 citations