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cs.CL2024
Matryoshka-Adaptor: Unsupervised and Supervised Tuning for Smaller Embedding Dimensions
Jinsung Yoon, Raj Sinha, Sercan O Arik +1
Embeddings from Large Language Models (LLMs) have emerged as critical components in various applications, particularly for information retrieval. While high-dimensional embeddings…
cs.CL2022★ 1 cited
BERT for Long Documents: A Case Study of Automated ICD Coding
Arash Afkanpour, Shabir Adeel, Hansenclever Bassani +11
Transformer models have achieved great success across many NLP problems. However, previous studies in automated ICD coding concluded that these models fail to outperform some of th…