papers

Publications (6)

cs.AI2026

DSpark: Confidence-Scheduled Speculative Decoding with Semi-Autoregressive Generation

Xin Cheng, Xingkai Yu, Chenze Shao +30

Speculative decoding accelerates Large Language Model (LLM) inference by decoupling draft generation from target verification. While recent parallel drafters efficiently propose lo…

cs.CR2025

How Would Oblivious Memory Boost Graph Analytics on Trusted Processors?

Jiping Yu, Xiaowei Zhu, Kun Chen +4

Trusted processors provide a way to perform joint computations while preserving data privacy. To overcome the performance degradation caused by data-oblivious algorithms to prevent…

cs.DB2024

GORAM: Graph-oriented ORAM for Efficient Ego-centric Queries on Federated Graphs

Xiaoyu Fan, Kun Chen, Jiping Yu +4

Ego-centric queries, focusing on a target vertex and its direct neighbors, are essential for various applications. Enabling such queries on graphs owned by mutually distrustful dat…

cs.DB2020

LiveGraph: A Transactional Graph Storage System with Purely Sequential Adjacency List Scans

Xiaowei Zhu, Guanyu Feng, Marco Serafini +5

The specific characteristics of graph workloads make it hard to design a one-size-fits-all graph storage system. Systems that support transactional updates use data structures with…

cs.CL2026

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

DeepSeek-AI, Anyi Xu, Bangcai Lin +315

We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…

cs.DC2021

DFOGraph: An I/O- and Communication-Efficient System for Distributed Fully-out-of-Core Graph Processing

Jiping Yu, Wei Qin, Xiaowei Zhu +4

With the magnitude of graph-structured data continually increasing, graph processing systems that can scale-out and scale-up are needed to handle extreme-scale datasets. While exis…