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cs.CL2024
Improving Structural Diversity of Blackbox LLMs via Chain-of-Specification Prompting
Halley Young, Yimeng Zeng, Jacob Gardner +1
The capability to generate diverse text is a key challenge facing large language models (LLMs). Thus far, diversity has been studied via metrics such as -gram diversity or diver…
cs.LG2024
Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity
Wentao Guo, Jikai Long, Yimeng Zeng +9
Zeroth-order optimization (ZO) is a memory-efficient strategy for fine-tuning Large Language Models using only forward passes. However, the application of ZO fine-tuning in memory-…
cs.LG2024★ 2 cited
Generative Adversarial Model-Based Optimization via Source Critic Regularization
Michael S. Yao, Yimeng Zeng, Hamsa Bastani +3
Offline model-based optimization seeks to optimize against a learned surrogate model without querying the true oracle objective function during optimization. Such tasks are commonl…