4 citations · 5 across the 6 of their papers we have counts for
6 papers
Nice Fold or Hero Call: Learning Budget-Efficient Thinking under Policy-Dependent Solvability
Zhaomeng Zhou, Lan Zhang, Junyang Wang +6
Large reasoning models (LRMs) improve problem solving through extended reasoning, but often misallocate test-time compute. Existing efficiency methods reduce cost by compressing re…
RemoteRAG: A Privacy-Preserving LLM Cloud RAG Service
Yihang Cheng, Lan Zhang, Junyang Wang +2
Retrieval-augmented generation (RAG) improves the service quality of large language models by retrieving relevant documents from credible literature and integrating them into the c…
Secure Transformer Inference Protocol
Mu Yuan, Lan Zhang, Xiang-Yang Li
Security of model parameters and user data is critical for Transformer-based services, such as ChatGPT. While recent strides in secure two-party protocols have successfully address…
MLink: Linking Black-Box Models from Multiple Domains for Collaborative Inference
Mu Yuan, Lan Zhang, Zimu Zheng +2
The cost efficiency of model inference is critical to real-world machine learning (ML) applications, especially for delay-sensitive tasks and resource-limited devices. A typical di…
InFi: End-to-End Learning to Filter Input for Resource-Efficiency in Mobile-Centric Inference
Mu Yuan, Lan Zhang, Fengxiang He +4
Mobile-centric AI applications have high requirements for resource-efficiency of model inference. Input filtering is a promising approach to eliminate the redundancy so as to reduc…
Comprehensive and Efficient Data Labeling via Adaptive Model Scheduling
Mu Yuan, Lan Zhang, Xiang-Yang Li +1
Labeling data (e.g., labeling the people, objects, actions and scene in images) comprehensively and efficiently is a widely needed but challenging task. Numerous models were propos…