2 citations · 3 across the 5 of their papers we have counts for
5 papers
Implicit Federated In-context Learning For Task-Specific LLM Fine-Tuning
Dongcheng Li, Junhan Chen, Aoxiang Zhou +4
As large language models continue to develop and expand, the extensive public data they rely on faces the risk of depletion. Consequently, leveraging private data within organizati…
Instant Resonance: Dual Strategy Enhances the Data Consensus Success Rate of Blockchain Threshold Signature Oracles
Youquan Xian, Xueying Zeng, Chunpei Li +4
With the rapid development of Decentralized Finance (DeFi) and Real-World Assets (RWA), the importance of blockchain oracles in real-time data acquisition has become increasingly p…
SEMSO: A Secure and Efficient Multi-Data Source Blockchain Oracle
Youquan Xian, Xueying Zeng, Chunpei Li +4
In recent years, blockchain oracle, as the key link between blockchain and real-world data interaction, has greatly expanded the application scope of blockchain. In particular, the…
Safeguarding the Truth of High-Value Price Oracle Task: A Dynamically Adjusted Truth Discovery Method
Youquan Xian, Peng Liu, Dongcheng Li +1
In recent years, the Decentralized Finance (DeFi) market has witnessed numerous attacks on the price oracle, leading to substantial economic losses. Despite the advent of truth dis…
FedDCT: A Dynamic Cross-Tier Federated Learning Framework in Wireless Networks
Youquan Xian, Xiaoyun Gan, Chuanjian Yao +4
Federated Learning (FL), as a privacy-preserving machine learning paradigm, trains a global model across devices without exposing local data. However, resource heterogeneity and in…