Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page
Demo Data from VLDB 2026 / reviewers in the wild / expert

Quanxing Dong

dblp:365/1676 · DBLP profile ↗
← Back
3ranked-venue papers
0as first author
3since 2021 · last 2026
0009-0008-2307-6047ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 since 2021Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%
Databases, data mining, and information retrieval
1 paper
Machine learning and data management · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing
cluster resource management and scheduling		 1.012026
Laser: Unlocking Layer-Level Scheduling for Efficient Multi-SLO LLM Serving · PPoPP 2026
Cloud and datacenter computing › inference serving
LLM inference scheduling		 1.012026
Laser: Unlocking Layer-Level Scheduling for Efficient Multi-SLO LLM Serving · PPoPP 2026
Cloud and datacenter computing › quality of service
SLO-aware scheduling		 1.012026
Laser: Unlocking Layer-Level Scheduling for Efficient Multi-SLO LLM Serving · PPoPP 2026
Machine learning and data management
data management for machine learning		 0.312026
Laser: Unlocking Layer-Level Scheduling for Efficient Multi-SLO LLM Serving · PPoPP 2026
Machine learning and data management › inference serving
LLM serving		 0.312026
Laser: Unlocking Layer-Level Scheduling for Efficient Multi-SLO LLM Serving · PPoPP 2026

Methods — techniques the papers use, named apart from their topics

layer-level scheduling · 2.0
YearPublicationVenuePosition
2026 Laser: Unlocking Layer-Level Scheduling for Efficient Multi-SLO LLM Serving
abstract
Engaging applications with diverse SLO requirements has become indispensable for production-scale LLM serving systems. However, existing systems rely on iteration-level scheduling, which enforces inflexible, unified execution across multi-SLO workloads, significantly constraining the serving efficiency.
Jianxiong Liao, Quanxing Dong, Yunkai Liang, Zhi Zhou 0006, Xu Chen 0004
 PPoPP2
2024 Medical image classification: Knowledge transfer via residual U-Net and vision transformer-based teacher-student model with knowledge distillation
Yucheng Song, Jincan Wang, Yifan Ge, Lifeng Li, Quanxing Dong, Zhifang Liao
 J. Vis. Commun. Image Represent.6
2023 Knowledge Distillation of Attention and Residual U-Net: Transfer from Deep to Shallow Models for Medical Image Classification
Zhifang Liao, Quanxing Dong, Yifan Ge, Huaiyi Chen, Yucheng Song
 PRCV (13)2