Papers by Yoonji Lee

1 papers
Plug-in and Fine-tuning: Bridging the Gap between Small Language Models and Large Language Models (2025.acl-long)

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Challenge: Large language models (LLMs) are renowned for their extensive linguistic knowledge and strong generalization capabilities, but their high computational demands make them unsuitable for resource-constrained environments.
Approach: They propose a framework that integrates a single frozen layer from an LLM into a SLM and fine-tunes the combined model for specific tasks.
Outcome: The proposed framework improves performance across a range of natural language processing tasks, including both natural language understanding and generation.

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