SHiFT: An Efficient, Flexible Search Engine for Transfer Learning
Summary: SHiFT: first downstream task-aware, flexible search engine over transfer-learning model repositories, exposing SHiFT-QL to express hybrid, task-specific model-selection criteria. Combines a cost-based optimizer and special incremental execution to evaluate queries efficiently for iterative ML workflows. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Cedric Renggli
- 2. Xiaozhe Yao
- 3. Luka Kolar
- 4. Luka Rimanic
- 5. Ana Klimovic
- 6. Ce Zhang
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,469 | Alsatian: Optimizing Model Search for Deep Transfer Learning | 2025 | SIGMOD | 4.1945683e-05 |
| 10,658 | LLMLog: Advanced Log Template Generation via LLM-driven Multi-Round Annotation | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,169 | QueryFormer: A Tree Transformer Model for Query Plan Representation | 2022 | VLDB | 7.4498425e-05 |
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| 3,320 | Schemaless and Structureless Graph Querying | 2014 | VLDB | 7.2249102e-05 |
| 10,154 | Distribution-Aware Exploration for Adaptive HNSW Search | 2026 | SIGMOD | 4.1945683e-05 |
| 9,139 | DataSift: A Crowd-Powered Search Toolkit | 2014 | SIGMOD | 4.3866006e-05 |
| 6,775 | A Unified Transferable Model for ML-Enhanced DBMS | 2022 | CIDR | 4.9299192e-05 |
| 2,170 | tf.data: A Machine Learning Data Processing Framework | 2021 | VLDB | 9.3821603e-05 |
| 9,776 | Structure-Aware Machine Learning over Multi-Relational Databases | 2021 | SIGMOD | 4.2856106e-05 |
| 5,258 | One Model to Rule them All: Towards Zero-Shot Learning for Databases | 2022 | CIDR | 5.5998705e-05 |
| 10,469 | Alsatian: Optimizing Model Search for Deep Transfer Learning | 2025 | SIGMOD | 4.1945683e-05 |