Papers with analysis of similarities

1 papers
Towards Unified Task Embeddings Across Multiple Models: Bridging the Gap for Prompt-Based Large Language Models and Beyond (2024.findings-acl)

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Challenge: Existing task embedding methods rely on fine-tuned, task-specific language models, which hinders their adaptability to prompt-guided Large Language Models (LLMs).
Approach: They propose a framework for unified task embedding that harmonizes task embeds from various models within a single vector space.
Outcome: The proposed framework harmonizes task embeddings from various models within a single vector space.

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