SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer | Paper Citation Record

Observation 15704861-2a98-4d89-ac8a-699385c17cd4 · outbound

This paper cites Many-shot in-context learning.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Many-shot in-context learning

Reference 1

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Observation 1eb5bd65-1355-413e-9362-95e05e26bdd5 · outbound

This paper cites The unreasonable effectiveness of LLMs for query optimization.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer The unreasonable effectiveness of LLMs for query optimization

Reference 2

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This paper cites What learning algorithm is in-context learning? Investigations with linear models.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer What learning algorithm is in-context learning? Investigations with linear models

Reference 3

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This paper cites https://www.tpc.org/tpcds/.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer https://www.tpc.org/tpcds/

Reference 4

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This paper cites A Robust and Explainable Query Optimization Cost Model Based on Bidirectional Graph Neural Networks.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer A Robust and Explainable Query Optimization Cost Model Based on Bidirectional Graph Neural Networks

Reference 5

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Observation cb9398f4-28bc-4139-b589-25fdfc20840c · outbound

This paper cites Loger: A learned optimizer towards generating efficient and robust query execution plans.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Loger: A learned optimizer towards generating efficient and robust query execution plans

Reference 6

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Observation 4bc8aac7-d7b7-4b65-8f55-6d857127b470 · outbound

This paper cites MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text

Reference 7

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Observation fe5972cd-cfb6-4704-8a5c-36896d593b4f · outbound

This paper cites Leon: A new framework for ml-aided query optimization.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Leon: A new framework for ml-aided query optimization

Reference 8

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Observation 637b2679-24fc-4020-984c-3a049b77bcb0 · outbound

This paper cites CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context

Reference 9

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Observation c10ea963-01cf-499d-a670-6336aa996747 · outbound

This paper cites Kepler: robust learning for parametric query optimization.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Kepler: robust learning for parametric query optimization

Reference 10

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Observation c6947614-4c62-4ff2-8637-76d15520166f · outbound

This paper cites Text-to-sql empowered by large language models: A benchmark evaluation.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Text-to-sql empowered by large language models: A benchmark evaluation

Reference 11

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Observation 4c4eb7de-cbfe-46fe-9789-4260a7604f7c · outbound

This paper cites Demonstrating -tune: Exploiting large language models for workload-adaptive database system tuning.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Demonstrating -tune: Exploiting large language models for workload-adaptive database system tuning

Reference 12

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Observation f9ec1f87-b008-4d42-967e-7fd482ee70e7 · outbound

This paper cites Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning

Reference 13

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Observation dc8d3ca8-75c6-4a7b-b216-be8cb5859a30 · outbound

This paper cites Retrieval augmented language model pre-training.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Retrieval augmented language model pre-training

Reference 14

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Observation fa29bd6f-ded0-49b5-95d6-a81b3fbe9f62 · outbound

This paper cites Transformer in transformer.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Transformer in transformer

Reference 15

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Observation df6e4627-fb22-431f-a6bb-d3ead8f463a9 · outbound

This paper cites Next-generation database interfaces: A survey of llm-based text-to-sql, 2025.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Next-generation database interfaces: A survey of llm-based text-to-sql, 2025

Reference 16

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Observation 48cb8f37-6c94-4d43-9377-a4372cf885f7 · outbound

This paper cites E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model

Reference 17

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Observation 9a79bb27-fa7a-44d0-96ae-45ce83a5c7d7 · outbound

This paper cites A survey on large language models for code generation, 2024.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer A survey on large language models for code generation, 2024

Reference 18

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Observation 4ba14edb-32fb-434e-b3d6-c63f9d9fc2a1 · outbound

This paper cites an unresolved cited work.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Unresolved cited work

Reference 19

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Observation dd165bab-70bc-46f0-a1ba-9845dcfcf320 · outbound

This paper cites On information and sufficiency.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer On information and sufficiency

Reference 20

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Observation 4ebe5b67-6e47-4dad-9120-f0f4500fcc00 · outbound

This paper cites GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization

Reference 21

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Observation 73ad7d0a-627c-431c-9813-e8ea5458c157 · outbound

This paper cites How good are query optimizers, really? Proceedings of the VLDB Endowment , 9(3):204--215, 2015.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer How good are query optimizers, really? Proceedings of the VLDB Endowment , 9(3):204--215, 2015

Reference 22

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Observation 52d4fd4e-1e89-46e7-8c63-d130c1bb8948 · outbound

This paper cites FVQA 2.0: Introducing Adversarial Samples into Fact-based Visual Question Answering.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer FVQA 2.0: Introducing Adversarial Samples into Fact-based Visual Question Answering

Reference 23

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Observation b094f9ca-abf6-4275-b8ed-dfde6bc00005 · outbound

This paper cites Serag: Self-evolving rag system for query optimization.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Serag: Self-evolving rag system for query optimization

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:55.064755Z

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Observation e093e8ff-e09a-4a8e-9f57-6a30479153f8 · outbound

This paper cites ReACC: A Retrieval-Augmented Code Completion Framework.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer ReACC: A Retrieval-Augmented Code Completion Framework

Reference 25

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Observation d8d78554-1528-4aa6-9ba4-fb5e3c7216b9 · outbound

This paper cites RaFe: Ranking Feedback Improves Query Rewriting for RAG.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer RaFe: Ranking Feedback Improves Query Rewriting for RAG

Reference 26

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Observation a1533cf9-4056-447f-bfd7-f6e8285df7eb · outbound

This paper cites FIT-RAG: Black-Box RAG with Factual Information and Token Reduction.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer FIT-RAG: Black-Box RAG with Factual Information and Token Reduction

Reference 27

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Observation 066d7d08-9a98-4b5a-8261-928d30ed5a10 · outbound

This paper cites Bao: Making learned query optimization practical.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Bao: Making learned query optimization practical

Reference 28

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Observation 371e4f32-f777-40b5-a865-715f543e2693 · outbound

This paper cites Neo: A learned query optimizer.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Neo: A learned query optimizer

Reference 29

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Observation e763dca1-804f-4612-9c28-fc338f85c155 · outbound

This paper cites Lemo: A cache-enhanced learned optimizer for concurrent queries.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Lemo: A cache-enhanced learned optimizer for concurrent queries

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:54.044773Z

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Observation ae898dc5-fbd3-40e9-b677-ba13a9d08265 · outbound

This paper cites Mysql 8.4.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Mysql 8.4

Reference 31

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Observation 3b342e35-860c-4167-acc2-75e256dfaa94 · outbound

This paper cites WebGPT: Browser-assisted question-answering with human feedback.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer WebGPT: Browser-assisted question-answering with human feedback

Reference 32

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Observation 2b0925b6-6707-40ec-9e61-df120771a197 · outbound

This paper cites A Comprehensive Overview of Large Language Models.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer A Comprehensive Overview of Large Language Models

Reference 33

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Observation 9d65c369-6ec5-4995-8209-645f6450a5bd · outbound

This paper cites Flow-loss: Learning cardinality estimates that matter.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Flow-loss: Learning cardinality estimates that matter

Reference 34

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Observation 407c5975-43f4-4a45-aa8e-0fe222ec4005 · outbound

This paper cites GPT-o3‑mini Model Documentation , 2025.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer GPT-o3‑mini Model Documentation , 2025

Reference 35

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Observation ac81e691-0e53-414e-b88b-3951632e7853 · outbound

This paper cites pg\_hint\_plan.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer pg\_hint\_plan

Reference 36

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Observation da9351d2-23b5-4a9c-972a-51fdcb56a39a · outbound

This paper cites Smaug: Fixing failure modes of preference optimisation with dpo-positive, 2024.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Smaug: Fixing failure modes of preference optimisation with dpo-positive, 2024

Reference 37

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Observation 813a954a-91f5-4144-8be1-3642d1037533 · outbound

This paper cites https://www.postgresql.org/.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer https://www.postgresql.org/

Reference 38

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Observation 34e20bc3-5608-4c95-9ae3-9fb8fc5a9f2c · outbound

This paper cites https://www.postgresql.org/.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer https://www.postgresql.org/

Reference 39

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Observation 31fad1ad-188c-4dd4-bf6e-c7799b6151b7 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Direct preference optimization: Your language model is secretly a reward model

Reference 40

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Observation bc3c7e5b-d9bc-4f23-8f65-d2c556b050ca · outbound

This paper cites Maximizing rag efficiency: A comparative analysis of rag methods.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Maximizing rag efficiency: A comparative analysis of rag methods

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:51.324763Z

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Observation deef5036-3ad7-4141-acb0-d6f4de5597d7 · outbound

This paper cites PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models

Reference 42

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Observation c1fc749e-6309-4632-ba0d-a0dc510a5c3c · outbound

This paper cites Proximal Policy Optimization Algorithms.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Proximal Policy Optimization Algorithms

Reference 43

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Observation 093f08a7-a3d3-47f5-9377-6e73a67ad619 · outbound

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SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Unresolved cited work

Reference 44

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Observation c43b80a8-18cc-4db3-a592-f8f1b6cadf57 · outbound

This paper cites Improving Retrieval-augmented Text-to-SQL with AST-based Ranking and Schema Pruning.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Improving Retrieval-augmented Text-to-SQL with AST-based Ranking and Schema Pruning

Reference 45

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Observation 76d1a6c2-b078-498d-bf75-7132dd85feb4 · outbound

This paper cites R-Bot: An LLM-based Query Rewrite System.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer R-Bot: An LLM-based Query Rewrite System

Reference 46

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Observation f906696d-12c4-447a-95c8-1f9b3ee34206 · outbound

This paper cites Vector database management systems: Fundamental concepts, use-cases, and current challenges.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Vector database management systems: Fundamental concepts, use-cases, and current challenges

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:51.020949Z

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Observation 5efb3b6c-b5c4-42a0-86b8-e70968824cdf · outbound

This paper cites Can Large Language Models Be Query Optimizer for Relational Databases?.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Can Large Language Models Be Query Optimizer for Relational Databases?

Reference 48

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Observation 090cfa5c-1c81-4d54-8e68-c1f877c05776 · outbound

This paper cites reads the manual.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer reads the manual

Reference 49

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Observation ccc9bd5d-8566-4111-b863-bf135905d529 · outbound

This paper cites Demonstrating gpt-db: Generating query-specific and customizable code for sql processing with gpt-4.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Demonstrating gpt-db: Generating query-specific and customizable code for sql processing with gpt-4

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:50.344758Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1717a8aa-5571-4ddc-a6db-ee752cfda906 · outbound

This paper cites Generating succinct descriptions of database schemata for cost-efficient prompting of large language models.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Generating succinct descriptions of database schemata for cost-efficient prompting of large language models

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:50.034839Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6fff0232-a1cc-4c97-87b5-c6e1170eae17 · outbound

This paper cites Generating highly customizable python code for data processing with large language models.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Generating highly customizable python code for data processing with large language models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:49.754864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation dab92933-4320-434b-bd30-a866cd5ac7a5 · outbound

This paper cites CAESURA: Language Models as Multi-Modal Query Planners.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer CAESURA: Language Models as Multi-Modal Query Planners

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-05T16:56:41.926392Z

Source-reported events for the cited work

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Observation c8d11c60-e313-4203-aec6-784cac027ae6 · outbound

This paper cites Milvus: A purpose-built vector data management system.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Milvus: A purpose-built vector data management system

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:49.464756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 74f5092c-6588-4eac-8465-c7e1e462e263 · outbound

This paper cites an unresolved cited work.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-05T16:56:49.178450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 770d0706-37a2-429b-81e0-a0d6fcb852df · outbound

This paper cites The learnability of in-context learning.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer The learnability of in-context learning

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:48.944757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d92ab533-efa6-4e51-95bb-905f1054d2e2 · outbound

This paper cites Fastgres: Making learned query optimizer hinting effective.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Fastgres: Making learned query optimizer hinting effective

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:48.604763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7b5b7113-d219-4855-af94-9a3f93a6b90a · outbound

This paper cites An Explanation of In-context Learning as Implicit Bayesian Inference.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer An Explanation of In-context Learning as Implicit Bayesian Inference

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-05T16:56:42.703822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d12c221b-28b7-4466-951a-7c55bafd16f3 · outbound

This paper cites Balsa: Learning a query optimizer without expert demonstrations.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Balsa: Learning a query optimizer without expert demonstrations

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:48.325058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b934e760-bb25-46f7-997d-12f1c35eed58 · outbound

This paper cites A Query Optimization Method Utilizing Large Language Models.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer A Query Optimization Method Utilizing Large Language Models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-05T16:56:43.049524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7632d1d9-1576-46a9-84ef-e4fb63229c24 · outbound

This paper cites Cost-based or learning-based? a hybrid query optimizer for query plan selection.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Cost-based or learning-based? a hybrid query optimizer for query plan selection

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:48.024758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c9b70061-a3b4-48db-89e6-88e519e919f1 · outbound

This paper cites Reinforcement learning with tree-lstm for join order selection.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Reinforcement learning with tree-lstm for join order selection

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:47.614754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b2c89358-f104-4762-bee6-e6c913c3d647 · outbound

This paper cites Refsql: A retrieval-augmentation framework for text-to-sql generation.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Refsql: A retrieval-augmentation framework for text-to-sql generation

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:47.254755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 34d38a4a-16cb-4125-8a6b-8251c3c1a9e6 · outbound

This paper cites Deploying a steered query optimizer in production at microsoft.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Deploying a steered query optimizer in production at microsoft

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:46.921209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 000ccbfb-6ac6-4b93-b904-a48e45f1b05f · outbound

This paper cites Lero: A learning-to-rank query optimizer.

SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer Lero: A learning-to-rank query optimizer

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:56:46.516265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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