1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CR2025
LLMail-Inject: A Dataset from a Realistic Adaptive Prompt Injection Challenge
Sahar Abdelnabi, Aideen Fay, Ahmed Salem +22
Indirect prompt injection attacks exploit a fundamental weakness of LLMs: executing unauthorized tasks from untrusted sources. Despite the practical significance of this attack vec…
cs.CL2024
Breaking the Ceiling of the LLM Community by Treating Token Generation as a Classification for Ensembling
Yao-Ching Yu, Chun-Chih Kuo, Ziqi Ye +2
Ensembling multiple models has always been an effective approach to push the limits of existing performance and is widely used in classification tasks by simply averaging the class…
cs.DC2022★ 1 cited
Improving Federated Learning Communication Efficiency with Global Momentum Fusion for Gradient Compression Schemes
Chun-Chih Kuo, Ted Tsei Kuo, Chia-Yu Lin
Communication costs within Federated learning hinder the system scalability for reaching more data from more clients. The proposed FL adopts a hub-and-spoke network topology. All c…