zeroth-order optimization

MaZO: Masked Zeroth-Order Optimization for Multi-Task Fine-Tuning of Large Language Models EMNLP 2025 Memory-Efficient Backpropagation for Fine-Tuning LLMs on Resource-Constrained Mobile Devices EMNLP 2025 MobiZO: Enabling Efficient LLM Fine-Tuning at the Edge via Inference Engines EMNLP 2025 MUZO: Leveraging Multiple Queries and Momentum for Zeroth-Order Fine-Tuning of Large Language Models EMNLP 2025 Natural Perturbations for Black-box Training of Neural Networks by Zeroth-Order Optimization ICML 2025 On the Inherent Privacy of Zeroth-Order Projected Gradient Descent AISTATS 2025 QuZO: Quantized Zeroth-Order Fine-Tuning for Large Language Models EMNLP 2025 Refining Adaptive Zeroth-Order Optimization at Ease ICML 2025 Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations ICLR 2025 Second-Order Fine-Tuning without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer ICLR 2025 Sharpness-aware Zeroth-order Optimization for Graph Transformers IJCAI 2025 Stability and Generalization of Zeroth-Order Decentralized Stochastic Gradient Descent with Changing Topology AAAI 2025 Towards Efficient Low-Order Hybrid Optimizer for Language Model Fine-Tuning AAAI 2025 Visualising Policy-Reward Interplay to Inform Zeroth-Order Preference Optimisation of Large Language Models ACL 2025 Zeroth-Order Fine-Tuning of LLMs in Random Subspaces ICCV 2025 Zeroth-Order Fine-Tuning of LLMs with Transferable Static Sparsity ICLR 2025 Zeroth-Order Methods for Nonconvex Stochastic Problems with Decision-Dependent Distributions AAAI 2025 Zeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference ICLR 2025 ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models ICLR 2025 AdaZeta: Adaptive Zeroth-Order Tensor-Train Adaption for Memory-Efficient Large Language Models Fine-Tuning EMNLP 2024 Bandits with Preference Feedback: A Stackelberg Game Perspective NeurIPS 2024 DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training ICLR 2024 Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient ICML 2024 Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes ICML 2024 General Stability Analysis for Zeroth-Order Optimization Algorithms ICLR 2024