Papers by Heshen Zhan
Unlocking Black-Box Prompt Tuning Efficiency via Zeroth-Order Optimization (2024.findings-emnlp)
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| Challenge: | Prompt optimization is an important technique for adapting Large Language Models (LLMs) to specific tasks. |
| Approach: | They propose a zeroth-order approach which enables efficient prompt tuning solely via inference APIs. |
| Outcome: | The proposed approach outperforms existing black-box prompt tuning methods in terms of performance and convergence speed. |