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20242026
most citedMooncake: A KVCache-centric Disaggregated Architecture for LLM Serving

13 citations · 18 across the 12 of their papers we have counts for

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7 papers · 1 filter

cs.AI2026

Coresets Before Score Sets: Evaluation-Unsupervised Prompt Subset Selection for LLM Benchmarks

Jihan Yao, Gantavya Bhatt, Arnav Das +16

We study LLM benchmark coreset selection: selecting a small subset of prompts over multiple benchmarks whose induced model scores and rankings approximate those obtained from the f…

cs.DC2026

TENT: A Declarative Slice Spraying Engine for Performant and Resilient Data Movement in Disaggregated LLM Serving

Feng Ren, Ruoyu Qin, Teng Ma +16

Modern GPU clusters rely on complex, heterogeneous interconnects. As large language model (LLM) serving shifts toward agentic reasoning, KVCache becomes a first-class mobile asset,…

cs.LG2026

SpecForge: A Flexible and Efficient Open-Source Training Framework for Speculative Decoding

Shenggui Li, Chao Wang, Yikai Zhu +14

Large language models incur high inference latency due to sequential autoregressive decoding. Speculative decoding alleviates this bottleneck by using a lightweight draft model to…

cs.NI2026

Not All Prefills Are Equal: PPD Disaggregation for Multi-turn LLM Serving

Zongze Li, Jingyu Liu, Zhen Xu +3

Prefill-Decode (PD) disaggregation has become the standard architecture for modern LLM inference engines, which alleviates the interference of two distinctive workloads. With the g…

cs.LG2026

When RL Meets Adaptive Speculative Training: A Unified Training-Serving System

Junxiong Wang, Fengxiang Bie, Jisen Li +14

Speculative decoding can significantly accelerate LLM serving, yet most deployments today disentangle speculator training from serving, treating speculator training as a standalone…

cs.CL2026

Understanding and Steering the Cognitive Behaviors of Reasoning Models at Test-Time

Zhenyu Zhang, Xiaoxia Wu, Zhongzhu Zhou +7

Large Language Models (LLMs) often rely on long chain-of-thought (CoT) reasoning to solve complex tasks. While effective, these trajectories are frequently inefficient, leading to…

cs.AI2026

FlashInfer-Bench: Building the Virtuous Cycle for AI-driven LLM Systems

Shanli Xing, Yiyan Zhai, Alexander Jiang +10

Recent advances show that large language models (LLMs) can act as autonomous agents capable of generating GPU kernels, but integrating these AI-generated kernels into real-world in…