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cs.CL2026
Steering the Noise: Turning Random Perturbations into Effective Descent for Memory-Efficient LLM Fine-Tuning
Feihu Jin, Shipeng Cen, Ying Tan
Fine-tuning large language models (LLMs) achieves strong performance but is often limited by the memory overhead of backpropagation. Zeroth-order (ZO) optimization avoids this over…
cs.CL2024
Derivative-Free Optimization for Low-Rank Adaptation in Large Language Models
Feihu Jin, Yin Liu, Ying Tan
Parameter-efficient tuning methods such as LoRA could achieve comparable performance to model tuning by tuning a small portion of the parameters. However, substantial computational…
cs.CL2024★ 5 cited
Zero-Shot Chain-of-Thought Reasoning Guided by Evolutionary Algorithms in Large Language Models
Feihu Jin, Yifan Liu, Ying Tan
Large Language Models (LLMs) have demonstrated remarkable performance across diverse tasks and exhibited impressive reasoning abilities by applying zero-shot Chain-of-Thought (CoT)…