collaborators

6 papers

cs.DC2026

HFX: Joint Design of Algorithms and Systems for Multi-SLO Serving and Fast Scaling

Zahra Yousefijamarani, Xinglu Wang, Qian Wang +12

Large language model (LLM) serving faces the dual challenge of meeting strict user-specific service-level objectives (SLOs) while minimizing computational cost under dynamic, multi…

cs.DC2026

Huawei Cloud Model-as-a-Service on the CloudMatrix384 SuperPod

Ao Xiao, Bangzheng He, Baoquan Zhang +125

Scaled-out MoE LLMs and scaled-up SuperPods create new systems challenges for production Model-as-a-Service (MaaS), requiring disaggregation, low-latency communication, and decentr…

cs.AI2026

DECKBench: Benchmarking Multi-Agent Frameworks for Academic Slide Generation and Editing

Daesik Jang, Morgan Lindsay Heisler, Linzi Xing +5

Automatically generating and iteratively editing academic slide decks requires more than document summarization. It demands faithful content selection, coherent slide organization,…

cs.LG2025

MEPIC: Memory Efficient Position Independent Caching for LLM Serving

Qian Wang, Zahra Yousefijamarani, Morgan Lindsay Heisler +8

Modern LLM applications such as deep-research assistants, coding agents, and Retrieval-Augmented Generation (RAG) systems, repeatedly process long prompt histories containing share…

cs.DC2025

Efficiently Serving Large Multimodal Models Using EPD Disaggregation

Gursimran Singh, Xinglu Wang, Yifan Hu +9

Large Multimodal Models (LMMs) extend Large Language Models (LLMs) by handling diverse inputs such as images, audio, and video, but at the cost of adding a multimodal encoding stag…

cs.LG2025

Enhancing Learned Knowledge in LoRA Adapters Through Efficient Contrastive Decoding on Ascend NPUs

Morgan Lindsay Heisler, Linzi Xing, Ge Shi +7

Huawei Cloud users leverage LoRA (Low-Rank Adaptation) as an efficient and scalable method to fine-tune and customize large language models (LLMs) for application-specific needs. H…