collaborators

8 papers

cs.DC2026

AFD-Ledger: Deployment Provisioning for Attention--FFN Disaggregation

Chengyu Qiu, Xiao Fu, Fengcun Li +6

Attention--Feed-Forward Network (FFN) Disaggregation (AFD) is emerging as a promising architecture for serving Mixture-of-Experts (MoE) language models. While existing AFD systems…

cs.DC2026

Surviving Partial Rank Failures in Wide Expert-Parallel MoE Inference

Xun Sun, Shaoyuan Chen, Pingchuan Ma +18

Mixture-of-Experts (MoE) serving relies on wide expert parallelism (EP) to aggregate the memory capacity and bandwidth of many GPUs within one inference instance. This efficiency c…

cs.CR2026

Order Flow Exclusivity and Value Extraction Mechanisms: An Analysis of Ethereum Builder Centralization

Ao Zhang, Yunwen Liu, Ren Zhang +2

This study investigates the rapid centralization of the Ethereum builder market under the Proposer-Builder Separation (PBS) architecture. We argue that existing research, by focusi…

cs.DC2026

Seer: Online Context Learning for Fast Synchronous LLM Reinforcement Learning

Ruoyu Qin, Weiran He, Weixiao Huang +7

Reinforcement Learning (RL) has emerged as a critical technique for advancing modern Large Language Models (LLMs), yet existing synchronous RL systems face severe performance bottl…

cs.DC2026

TrEnv-X: Transparently Share Serverless Execution Environments Across Different Functions and Nodes

Jialiang Huang, Teng Ma, Zheng Liu +11

Serverless computing is renowned for its computation elasticity, yet its full potential is often constrained by the requirement for functions to operate within local and dedicated…

cs.DC2025

Efficient Graph-Based Approximate Nearest Neighbor Search Achieving: Low Latency Without Throughput Loss

Jingjia Luo, Mingxing Zhang, Kang Chen +4

The increase in the dimensionality of neural embedding models has enhanced the accuracy of semantic search capabilities but also amplified the computational demands for Approximate…