Papers by Tamara Czinczoll

2 papers
Scientific and Creative Analogies in Pretrained Language Models (2022.findings-emnlp)

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Challenge: Existing analogy datasets focus on a limited set of analogical relations with a high similarity of the two domains between which the analogy holds.
Approach: They propose a dataset that encodes analogy in pretrained language models . they use a system that maps attributes and relational structures across dissimilar domains .
Outcome: The proposed dataset shows that state-of-the-art models achieve low performance on analogy tasks .
NextLevelBERT: Masked Language Modeling with Higher-Level Representations for Long Documents (2024.acl-long)

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Challenge: (large) language models struggle to process long sequences due to the quadratic scaling of the underlying attention mechanism.
Approach: They propose a Masked Language Model operating on higher-level semantic representations in the form of text embeddings to solve this problem.
Outcome: The proposed model outperforms larger embedding models on three types of tasks.

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