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CAESURA: Language Models as Multi-Modal Query Planners
Summary: Introduces Language-Model-Driven Query Planning: use LMs to translate natural-language queries into executable multi-modal query plans with operators over arbitrary modalities (images, text, video), unlike traditional SQL planners. Presents CAESURA, a GPT-4 prototype demonstrating feasibility on two datasets and proposing techniques to improve LM planning robustness for end-to-end multi-modal query execution.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 505
- Venue
- CIDR
- Year
- 2024
- Pagerank
- 0.00014214232
- Overall Rank
- 1,082 | 92.48%
- DOI
-
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Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 23 of 23 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 1,872 |
ReAcTable: Enhancing ReAct for Table Question Answering |
2024 |
VLDB |
0.00010259702 |
| 1,963 |
DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing |
2025 |
VLDB |
9.929429e-05 |
| 2,106 |
Palimpzest: Optimizing AI-Powered Analytics with Declarative Query Processing |
2025 |
CIDR |
9.5342543e-05 |
| 3,876 |
The Design of an LLM-powered Unstructured Analytics System |
2025 |
CIDR |
6.6741456e-05 |
| 5,171 |
Abacus: A Cost-Based Optimizer for Semantic Operator Systems |
2026 |
VLDB |
5.6464993e-05 |
| 5,658 |
Databases Unbound: Querying All of the World's Bytes with AI |
2024 |
VLDB |
5.385675e-05 |
| 5,840 |
Logical and Physical Optimizations for SQL Query Execution over Large Language Models |
2025 |
SIGMOD |
5.3042561e-05 |
| 7,705 |
AOP: Automated and Interactive LLM Pipeline Orchestration for Answering Complex Queries |
2025 |
CIDR |
4.6730494e-05 |
| 8,204 |
ELEET: Efficient Learned Query Execution over Text and Tables |
2024 |
VLDB |
4.5594273e-05 |
| 8,488 |
Can Large Language Models Be Query Optimizer for Relational Databases? |
2026 |
SIGMOD |
4.4998609e-05 |
| 8,736 |
Unveiling Challenges for LLMs in Enterprise Data Engineering |
2026 |
VLDB |
4.456315e-05 |
| 9,370 |
PalimpChat: Declarative and Interactive AI analytics |
2025 |
SIGMOD |
4.3480692e-05 |
| 9,729 |
Semantic Integrity Constraints: Declarative Guardrails for AI-Augmented Data Processing Systems |
2025 |
VLDB |
4.2942813e-05 |
| 9,972 |
KathDB: Explainable Multimodal Database Management System with Human-AI Collaboration |
2026 |
CIDR |
4.1945683e-05 |
| 9,990 |
Deep Research is the New Analytics System: Towards Building the Runtime for AI-Driven Analytics |
2026 |
CIDR |
4.1945683e-05 |
| 9,994 |
BridgeScope: A Universal Toolkit for Bridging Large Language Models and Databases |
2026 |
CIDR |
4.1945683e-05 |
| 10,064 |
Cut Costs, Not Accuracy: LLM-Powered Data Processing with Guarantees |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,112 |
SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,144 |
Beyond Relational: Semantic-Aware Multi-Modal Analytics with LLM-Native Query Optimization |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,212 |
SQLBarber: A System Leveraging Large Language Models to Generate Customized and Realistic SQL Workloads |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,215 |
Task Cascades for Efficient Unstructured Data Processing |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,752 |
QUEST: Query Optimization in Unstructured Document Analysis |
2025 |
VLDB |
4.1945683e-05 |
| 10,800 |
Unify: A System For Unstructured Data Analytics |
2025 |
VLDB |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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