From the 1 of 7 linked papers with an AI index.
1 citations · 1 across the 1 of their papers we have counts for
7 papers
When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?
Shang Wang, Tianqing Zhu, Dayong Ye +1
The paper proposes a lightweight method to make large language models forget specific information by altering the external knowledge base of Retrieval‑Augmented Generation systems,…
Elastic Architecture Search for Efficient Language Models
Shang Wang
As large pre-trained language models become increasingly critical to natural language understanding (NLU) tasks, their substantial computational and memory requirements have raised…
Unique Security and Privacy Threats of Large Language Models: A Comprehensive Survey
Shang Wang, Tianqing Zhu, Bo Liu +4
With the rapid development of artificial intelligence, large language models (LLMs) have made remarkable advancements in natural language processing. These models are trained on va…
Towards Generalized Routing: Model and Agent Orchestration for Adaptive and Efficient Inference
Xiyu Guo, Shan Wang, Chunfang Ji +6
The rapid advancement of large language models (LLMs) and domain-specific AI agents has greatly expanded the ecosystem of AI-powered services. User queries, however, are highly div…
W-PCA Based Gradient-Free Proxy for Efficient Search of Lightweight Language Models
Shang Wang
The demand for efficient natural language processing (NLP) systems has led to the development of lightweight language models. Previous work in this area has primarily focused on ma…
Data-Free Model-Related Attacks: Unleashing the Potential of Generative AI
Dayong Ye, Tianqing Zhu, Shang Wang +4
Generative AI technology has become increasingly integrated into our daily lives, offering powerful capabilities to enhance productivity. However, these same capabilities can be ex…