Powering In-Database Dynamic Model Slicing for Structured Data Analytics
Summary: LEADS: SQL-aware dynamic model slicing that trains a Mixture-of-Experts over relational data and uses a SQL-aware gating network to activate experts per SQL query, customizing models to extracted subdatasets. Implemented as a PostgreSQL inference extension, yielding better accuracy and much lower latency. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Lingze Zeng
- 2. Naili Xing
- 3. Shaofeng Cai
- 4. Gang Chen
- 5. Beng Chin Ooi
- 6. Jian Pei
- 7. Yuncheng Wu
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,688 | NeurDB: On the Design and Implementation of an AI-powered Autonomous Database | 2025 | CIDR | 4.4673127e-05 |
| 10,095 | NeurStore: Efficient In-database Deep Learning Model Management System | 2026 | SIGMOD | 4.1945683e-05 |
| 10,100 | AixelNet: A Pre-trained Model with Table-aware Adaptation for Structured Data Prediction | 2026 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 15 of 15 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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