FaDE: More Than a Million What-ifs Per Second
Summary: FaDE compiles provenance into relational evaluation plans (not symbolic expressions) to evaluate deletion/scaling interventions at low latency. With compilation, parallel, incremental and sparse evaluation it yields ~1000x vs IVM, ~10000x vs prior provenance and >1M interventions/sec. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Haneen Mohammed
- 2. Alexander Yao
- 3. Charlie Summers
- 4. Hongbin Zhong
- 5. Gromit Yeuk-Yin Chan
- 6. Subrata Mitra
- 7. Lampros Flokas
- 8. Eugene Wu
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,968 | Please Don't Kill My Vibe: Empowering Agents with Data Flow Control | 2026 | CIDR | 4.1945683e-05 |
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