1 citations · 2 across the 8 of their papers we have counts for
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Scalable and Interpretable Representation Alignment with Ordinal Similarity
Diogo Soares, Pankhil Gawade, Andrea Dittadi +1
Evaluating representation similarity is fundamental to representation learning. However, existing metrics suffer from significant limitations: they lack interpretability due to shi…
Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics
Egor Antipov, Alessandro Palma, Lorenzo Consoli +3
Estimating density ratios between pairs of intractable data distributions is a core problem in probabilistic modeling, enabling principled comparisons of sample likelihoods under d…
From Words to Amino Acids: Does the Curse of Depth Persist?
Aleena Siji, Amir Mohammad Karimi Mamaghan, Ferdinand Kapl +9
Protein language models (PLMs) have become widely adopted as general-purpose models, demonstrating strong performance in protein engineering and de novo design. Like large language…
Does Data Scaling Lead to Visual Compositional Generalization?
Arnas Uselis, Andrea Dittadi, Seong Joon Oh
Compositional understanding is crucial for human intelligence, yet it remains unclear whether contemporary vision models exhibit it. The dominant machine learning paradigm is built…