Search Results for author: Zihan Fang

Found 4 papers, 0 papers with code

Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models

no code implementations9 Apr 2024 Zihan Fang, Zheng Lin, Zhe Chen, Xianhao Chen, Yue Gao, Yuguang Fang

Recently, there has been a surge in the development of advanced intelligent generative content (AIGC), especially large language models (LLMs).

Federated Learning Privacy Preserving

AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learning

no code implementations9 Apr 2024 Senkang Hu, Zhengru Fang, Zihan Fang, Yiqin Deng, Xianhao Chen, Yuguang Fang

In addition, the single-vehicle autonomous driving systems lack of the ability of collaboration and negotiation with other vehicles, which is crucial for the safety and efficiency of autonomous driving systems.

Autonomous Driving Language Modelling +1

FedSN: A Novel Federated Learning Framework over LEO Satellite Networks

no code implementations2 Nov 2023 Zheng Lin, Zhe Chen, Zihan Fang, Xianhao Chen, Xiong Wang, Yue Gao

To this end, we propose FedSN as a general FL framework to tackle the above challenges, and fully explore data diversity on LEO satellites.

Federated Learning Image Classification +1

Bridging Trustworthiness and Open-World Learning: An Exploratory Neural Approach for Enhancing Interpretability, Generalization, and Robustness

no code implementations7 Aug 2023 Shide Du, Zihan Fang, Shiyang Lan, Yanchao Tan, Manuel Günther, Shiping Wang, Wenzhong Guo

As researchers strive to narrow the gap between machine intelligence and human through the development of artificial intelligence technologies, it is imperative that we recognize the critical importance of trustworthiness in open-world, which has become ubiquitous in all aspects of daily life for everyone.

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