ELEET: Efficient Learned Query Execution over Text and Tables
Summary: ELEET makes text first-class via learned multi-modal operators (MMOps), enabling native joins/unions over tables and unstructured text. Replacing LLMs with a compact SLM and tailored pretraining, ELEET extracts structure with low overhead and achieves up to 575× speedups vs GPT‑4 baselines without accuracy loss. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Matthias Urban
- 2. Carsten Binnig
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,971 | KathDB: Explainable Multimodal Database Management System with Human-AI Collaboration | 2026 | CIDR | 4.1905499e-05 |
| 10,064 | Cut Costs, Not Accuracy: LLM-Powered Data Processing with Guarantees | 2026 | SIGMOD | 4.1905499e-05 |
| 10,215 | Task Cascades for Efficient Unstructured Data Processing | 2026 | SIGMOD | 4.1905499e-05 |
| 10,285 | Relational Deep Dive: Error-Aware Queries Over Unstructured Data | 2026 | VLDB | 4.1905499e-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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