1 citations · 2 across the 5 of their papers we have counts for
5 papers
HoneyRoute: Honeypot-Model Routing for Adversarial LLM Serving
Han Jin
We introduce HoneyRoute, an inference-serving layer that detects whether an incoming request is malicious and, if so, routes it to a dedicated honeypot model, shielding production…
Alopex: A Computational Framework for Enabling On-Device Function Calls with LLMs
Yide Ran, Zhaozhuo Xu, Yuhang Yao +9
The rapid advancement of Large Language Models (LLMs) has led to their increased integration into mobile devices for personalized assistance, which enables LLMs to call external AP…
ScaleLLM: A Resource-Frugal LLM Serving Framework by Optimizing End-to-End Efficiency
Yuhang Yao, Han Jin, Alay Dilipbhai Shah +7
Large language models (LLMs) have surged in popularity and are extensively used in commercial applications, where the efficiency of model serving is crucial for the user experience…
TensorOpera Router: A Multi-Model Router for Efficient LLM Inference
Dimitris Stripelis, Zijian Hu, Jipeng Zhang +6
With the rapid growth of Large Language Models (LLMs) across various domains, numerous new LLMs have emerged, each possessing domain-specific expertise. This proliferation has high…
FedSecurity: Benchmarking Attacks and Defenses in Federated Learning and Federated LLMs
Shanshan Han, Baturalp Buyukates, Zijian Hu +13
This paper introduces FedSecurity, an end-to-end benchmark that serves as a supplementary component of the FedML library for simulating adversarial attacks and corresponding defens…