Papers by Daniel Biś

2 papers
Too Much in Common: Shifting of Embeddings in Transformer Language Models and its Implications (2021.naacl-main)

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Challenge: Existing studies have shown that word embeddings do not occupy a narrow cone, but rather drift in common directions.
Approach: They show that anisotropy can be restored using a simple transformation of word embeddings.
Outcome: The proposed model can restore anisotropy using a simple transformation.
PAIGE: Personalized Adaptive Interactions Graph Encoder for Query Rewriting in Dialogue Systems (2022.emnlp-industry)

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Challenge: Existing methods to fix faulty queries are limited in their ability to fix them.
Approach: They propose a Personalized Adaptive Interactions Graph Encoder that integrates user's affinities and query semantics to refine utterance embeddings.
Outcome: The proposed Query Rewriting (QR) techniques improve the rewrite accuracy of state-of-the-art baselines by 12.5–17.5% while having nearly ten times fewer parameters.

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