Papers by Tobias Stollenwerk

1 papers
Better Embeddings with Coupled Adam (2025.acl-long)

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Challenge: Anisotropic Embeddings Large Language Models exhibit undesirable yet poorly understood feature of anisotropy.
Approach: They propose an algorithm that uses the second moment in Adam to mitigate anisotropic embeddings . they propose an embeddable matrix and unembedding matrix to map the input and output tokens based on weight tying .
Outcome: The proposed model improves quality and performance on large datasets.

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