Papers with task-specific modulator

1 papers
Feature-Adaptive and Data-Scalable In-Context Learning (2024.acl-long)

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Challenge: In-context learning (ICL) is a popular way to stimulate LLM capabilities for downstream tasks due to context length constraints.
Approach: They propose a feature-adaptive and data-scalable in-context learning framework which leverages task-adaptives to promote inference on the downstream task.
Outcome: The proposed framework outperforms state-of-the-art methods on 10 datasets under different data settings and LLM scale.

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