Papers by Lijuan Sun

1 papers
Spotlighter: Revisiting Prompt Tuning from a Representative Mining View (2025.findings-emnlp)

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Challenge: Spotlighter is a lightweight token-selection framework that enhances accuracy and efficiency in prompt tuning.
Approach: They propose a token-selection framework that enhances accuracy and efficiency in prompt tuning by preserving only the top-scoring tokens for downstream prediction.
Outcome: The proposed framework outperforms CLIP by up to 11.19% in harmonic mean accuracy and achieves 0.8K additional FPS, with only 21 extra parameters.

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