Papers with representation-based and generation-based relevance scores

1 papers
ULLME: A Unified Framework for Large Language Model Embeddings with Generation-Augmented Learning (2024.emnlp-demo)

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Challenge: Existing frameworks for large language model embeddings have limited support for only a limited range of architectures and fine-tuning strategies.
Approach: They propose a framework that enables bidirectional attention across various LLMs and supports a range of fine-tuning strategies.
Outcome: The proposed framework enables bidirectional attention across various LLMs and supports a range of fine-tuning strategies.

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