14 citations · 20 across the 12 of their papers we have counts for
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cs.DC2025
ConsumerBench: Benchmarking Generative AI Applications on End-User Devices
Yile Gu, Rohan Kadekodi, Hoang Nguyen +3
The recent shift in Generative AI (GenAI) applications from cloud-only environments to end-user devices introduces new challenges in resource management, system efficiency, and use…
cs.DC2025★ 1 cited
TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval
Chien-Yu Lin, Keisuke Kamahori, Yiyu Liu +11
Retrieval-augmented generation (RAG) extends large language models (LLMs) with external data sources to enhance factual correctness and domain coverage. Modern RAG pipelines rely o…
cs.DC2024★ 1 cited
NanoFlow: Towards Optimal Large Language Model Serving Throughput
Kan Zhu, Yufei Gao, Yilong Zhao +13
Large Language Models (LLMs) have resulted in a surging demand for planet-scale serving systems, where tens of thousands of GPUs continuously serve hundreds of millions of users. C…