2 papers
cs.CL2025
Enabling Flexible Multi-LLM Integration for Scalable Knowledge Aggregation
Zhenglun Kong, Zheng Zhan, Shiyue Hou +10
Large language models (LLMs) have shown remarkable promise but remain challenging to continually improve through traditional finetuning, particularly when integrating capabilities…
cs.CL2024
FedDTPT: Federated Discrete and Transferable Prompt Tuning for Black-Box Large Language Models
Jiaqi Wu, Simin Chen, Yuzhe Yang +6
In recent years, large language models (LLMs) have significantly advanced the field of natural language processing (NLP). By fine-tuning LLMs with data from specific scenarios, the…