2 papers
cs.LG2025
Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning
Yujia Huo, Jianchun Liu, Hongli Xu +3
Federated fine-tuning (FedFT) of large language models (LLMs) has emerged as a promising solution for adapting models to distributed data environments while ensuring data privacy.…
cs.CL2024
Logic Contrastive Reasoning with Lightweight Large Language Model for Math Word Problems
Ding Kai, Ma Zhenguo, Yan Xiaoran
This study focuses on improving the performance of lightweight Large Language Models (LLMs) in mathematical reasoning tasks. We introduce a novel method for measuring mathematical…