Papers by Çağatay Yıldız

2 papers
A Reproduction Study: The Kernel PCA Interpretation of Self-Attention Fails Under Scrutiny (2025.acl-srw)

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Challenge: Recent studies suggest that self-attention implements kernel principal component analysis (KPCA) Across 10 transformer architectures, we conclude that the KPCA interpretation of self- attention lacks empirical support.
Approach: They revisit claims that self-attention implements kernel principal component analysis . they argue that self attention projects queries onto principal component axes of key matrix K .
Outcome: The proposed kernel principal component analysis does not match the proposed kernel . the proposed method is not able to detect the eigenvalues of the gram matrix .
Adaptation Odyssey in LLMs: Why Does Additional Pretraining Sometimes Fail to Improve? (2024.emnlp-main)

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Challenge: In the last decade, the generalization and adaptation abilities of deep learning models were evaluated on fixed training and test distributions.
Approach: They propose to train large language models on unlabeled text corpora and train them online.
Outcome: The proposed model training on a text domain could degrade its perplexity on the test portion of the same domain.

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