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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 0 inbound Pith citation observations for arXiv:2508.17556.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.17556 v1

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:56:43.604758Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

65 of 65 outbound references displayed

  • verified exact2
  • verified fuzzy40
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:34.104756Z digest=sha256:287f82ada527ead913708dff1dc66f54ddbc8fadbff4b0928de338fbe0163fab

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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raw_fallback, observed 2026-08-05T16:56:59.484793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:34.284754Z digest=sha256:8ae68a4769188040c91f4a70a10e2a5e71883c8c24862deb13aa82023f51c436

Observation 5527dd81-bc3d-4f1b-8f35-6a70e5300a1f · outbound

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:34.481262Z digest=sha256:497a7150fe12284c997275debadecb9f861f143b4555c9097bb9934b298601c1

Observation 12f65048-7db3-4ddc-a837-956b9e662548 · outbound

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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raw_fallback, observed 2026-08-05T16:56:59.184844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:34.626545Z digest=sha256:971eeadef65463496e0221f410164263c2bda3df29e0be76d92ff93bbe7c855d

Observation 609a57ee-2c34-4452-b9f9-37fa642f92a8 · outbound

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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raw_fallback, observed 2026-08-05T16:56:58.844760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:34.775491Z digest=sha256:c18ea2bb206db4507e2e500040fae4b65e75a16ba0707ded8cc7078b95d02194

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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raw_fallback, observed 2026-08-05T16:56:58.529684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:34.914857Z digest=sha256:5638264a352a248b30401bd5c643458b67bdf40232ade69970d12e6122ce13f2

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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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-05T16:56:35.133188Z digest=sha256:b249d8f4ed69b008ea3383e60f1300e90f474a3e19d043351c0984afbd3c8f1b

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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raw_fallback, observed 2026-08-05T16:56:58.172109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:35.262166Z digest=sha256:004d624654c332c38cb5daf9a0b73a75d7df52ba84da5f1ca13a168074536f8e

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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source=arxiv_source observed=2026-08-05T16:56:35.409533Z digest=sha256:b54f34a66878378f63ee2a1958c58b7f3eacefd598fe405c9271d2632d6392ee

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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verified fuzzy
raw_fallback, observed 2026-08-05T16:56:57.740062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:35.554758Z digest=sha256:7289d1c43db9882ea7ac4e3ba6e28e261624d86af8b8c6276db59546a95d69d5

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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raw_fallback, observed 2026-08-05T16:56:57.324749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:35.694756Z digest=sha256:20f61f4ff986efac8a9915c0a0975017e59942a2edfe9b6021bfed4815a17083

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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verified fuzzy
raw_fallback, observed 2026-08-05T16:56:56.945309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:35.844757Z digest=sha256:9c403ce2db7c20150dbedc94105dae0aa073040b92755fc07d626e0cdf3f9f92

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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source=arxiv_source observed=2026-08-05T16:56:36.023552Z digest=sha256:8ddd4ac19c333ebee984d41d40ba64f1077fca37d3d870362b40dc5d3c0fb394

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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verified fuzzy
raw_fallback, observed 2026-08-05T16:56:56.694861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:36.144846Z digest=sha256:e78e5a85ca43f0f911632c092701f6c5d0972b5f605c326ef7ad9fab94e77b14

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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raw_fallback, observed 2026-08-05T16:56:56.164754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:36.258250Z digest=sha256:9172b379deb8952306c5c81bb5f4eed6585e13755faa99ed534c41df0bb17277

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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raw_fallback, observed 2026-08-05T16:56:55.890437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:36.484745Z digest=sha256:894a8becb000499fe7b45e9cb42ab4c533f4b948904a21ffd171fd4775d835d5

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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source=arxiv_source observed=2026-08-05T16:56:36.690505Z digest=sha256:bf1b65732886797c019874031fca92bee2add2c6461449b99d2ab8e633710a8e

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:36.826437Z digest=sha256:86a2359497e6aeb47cc0e1186efe636a69459e4d7fc4f190c99e086e38a92954

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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source=arxiv_source observed=2026-08-05T16:56:36.984939Z digest=sha256:33dc82afd0b59e6ea69549eb31346efa14e9564abbca74fa238da378ab999911

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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source=arxiv_source observed=2026-08-05T16:56:37.145881Z digest=sha256:95c9e9e7a706bf245ea0891edae475fe1810d4b243b9eb1f640fb3594c12dc93

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:37.191916Z digest=sha256:14f30e1499eabdffff655c32270814dc5c77185fd98da9e0e3e57f191d69ca0d

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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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:37.374769Z digest=sha256:14501e3ffdaca672e51072f6d1e335766843136cb32bdcb3b1e1b5e770d68012

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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local_arxiv, observed 2026-08-05T16:56:45.090310Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:37.561590Z digest=sha256:3d2e475b24aabe725640546e57b3c3df6b8172608108ca99fab08226ea1c3778

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

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raw_fallback, observed 2026-08-05T16:56:55.064755Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:37.723458Z digest=sha256:c29196491473d131749ea3ae70d4e1c582cb1d9321eb5d600e18e5298953ab0c

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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source=arxiv_source observed=2026-08-05T16:56:37.924748Z digest=sha256:ff06ef16976524c29c29728894c1527e7f7164ae7bea7efdd31aeaecd608efc4

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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no resolver link, observed 2026-08-05T16:56:38.050540Z

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source=arxiv_source observed=2026-08-05T16:56:38.050540Z digest=sha256:8f39d1814dde596928e338183e5c6b4a90d68ccc08e13a9ced16291a901235a8

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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local_arxiv, observed 2026-08-05T16:56:44.316118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:38.145022Z digest=sha256:6e382a396381581e0fca0fddbe7ea06bea02a880cadb4cb2958a5c9317eeec5e

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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raw_fallback, observed 2026-08-05T16:56:54.744762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:38.221187Z digest=sha256:0ac8643b9d51a5400afb74f987d5113b09f9c0a2f1d4a1e2e4f9093ecd809dd2

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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raw_fallback, observed 2026-08-05T16:56:54.394754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:38.334745Z digest=sha256:5a7689303a0c209c6a6a6acc844dc651b648c3d85c932022463e8cc975130ecf

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

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raw_fallback, observed 2026-08-05T16:56:54.044773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:38.454773Z digest=sha256:41687c32b6f7c86e6fdded0740366d2b0ab1e1738c9f13b274c419f2ba36c7f8

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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raw_fallback, observed 2026-08-05T16:56:53.714759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:38.617488Z digest=sha256:6d538b5f750bfbf3281a126d4933c67c9362aa6caefd613c24978dfd0b5b075a

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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no resolver link, observed 2026-08-05T16:56:38.804753Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:38.804753Z digest=sha256:6ebd67f70d0d896f36ce3b2c6f52a54abab872def59bf7104809a824ea502724

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:38.954750Z digest=sha256:692d1a76926142ac6e315e8a252d57a76ddf328337608be0913b7ebd7f9b83b2

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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verified fuzzy
raw_fallback, observed 2026-08-05T16:56:53.404756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:39.072509Z digest=sha256:1deee42297e4920241ddd003fe36e1ef15a8f1d7abba0a717bef41e373d3f5cb

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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verified fuzzy
raw_fallback, observed 2026-08-05T16:56:53.004794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:39.231735Z digest=sha256:f10ff15e781661664cf76756c1598dfe6269826226648d93f0959cfe86623efe

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:56:52.594756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:39.424754Z digest=sha256:2813ce1c0b17f711157c2b17c13d5686b6b5f270561715e2eed2bb409181c897

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

Resolution
unresolved
no resolver link, observed 2026-08-05T16:56:39.613663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:39.613663Z digest=sha256:62a9f656915e73eb611b30f43057d66cf4800bd4eb116f9887811a23ac2116f9

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:56:52.273951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:39.794754Z digest=sha256:672782605a11929a24f341eecdbdc6bd4b84ee61b35851cd040f3477be2e643a

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:56:52.024757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:39.924019Z digest=sha256:321057fc5b4986ed018f7c6fb104acac3d53cdcfaeabe5dee13a30b120bffc43

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:56:51.598126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:40.054935Z digest=sha256:32a19ef038f8cfc3cd5fdb1a82a48662837d44e565d3645486d21e22887ff8a1

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:40.174843Z digest=sha256:e0e3a0fe1df918017e89f0230c01c3bb17efbbf2799c82d1b4f14f1d00f8ca26

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

Resolution
unresolved
no resolver link, observed 2026-08-05T16:56:40.274500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:40.274500Z digest=sha256:53697b3966b1e8686a0417693b50dbf0dca3d3dcbdf0c135d1e218e1d0d857a8

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

Resolution
unresolved
no resolver link, observed 2026-08-05T16:56:40.404754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:40.404754Z digest=sha256:8a0fd950f9ec4f47d062a2574431545dbe811fc23f41df4c0b2dfba3320b19ed

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

This paper cites an unresolved cited work.

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

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-05T16:56:40.564769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:40.564769Z digest=sha256:e0fcb70fadc9634d67ba618bf814241398c80c21b345496bb7ce12abf00ab2a2

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

Resolution
unresolved
no resolver link, observed 2026-08-05T16:56:40.714834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:40.714834Z digest=sha256:76e839e915ce9975d7e5603cbce086a253fa829a3363e613c6f1432595c9fadb

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

Resolution
unresolved
no resolver link, observed 2026-08-05T16:56:40.884758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:40.884758Z digest=sha256:8e3e7fc6a0d55f3129d13adf98e428bf12038b74123f8230217f7a964046806c

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:41.054907Z digest=sha256:2b264d4b3a2378857b9cd581c3ed8f06c93799b39d8f8cb569f1d564190240d3

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

Resolution
unresolved
no resolver link, observed 2026-08-05T16:56:41.243776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:41.243776Z digest=sha256:e38d4eb0a66303428966cb94c4c737ee486f2ed1874c953017f5ac2d6c8de432

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:56:50.704855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:41.375449Z digest=sha256:71645456e342f3e974839a4f0fe6e9bfead2a4bfd10032b70b1c37145b12850d

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:41.471126Z digest=sha256:d5c3f45dd56f17c91c0434c6dbbbc4f59582e244c58be015a3f6055e84144b79

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:41.644756Z digest=sha256:549e4e8aaf81b6dc67bf4d52916957eec6ed5eacbac9d527b763952e384a2036

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:41.764757Z digest=sha256:2c046c8ce66573f8b83f2f9dc9815e54040eed060f45a55045ba5782f92869a7

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

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:41.926392Z digest=sha256:3220ed18ff22e8b96b80ae8cfb28e84fad5ee35bb3a7b36b49899f8337ddd8ce

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:42.095167Z digest=sha256:04b654c758f25d69c87414b1a73c93694338bc2a8f5d09a9d36158be7ef8cd2c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:42.234760Z digest=sha256:36342eeb21869ebae7f4137db2da4d7f33ed86507da69485446544ecca81132b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:42.384760Z digest=sha256:fb3714d798fef27a7dee816e2b26926d52bee8d0dd8cd8ca2a535390f1fb8e25

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:42.495068Z digest=sha256:6c259a4e863dbcdd9fafb4b26f5d8b472df38330a416f4d3f09bfb797c774649

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.

source=arxiv_source observed=2026-08-05T16:56:42.703822Z digest=sha256:699e003c8b4461ca22aaf0b95c2a527192333e292e6dee60a8b2cd4273152fe6

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:42.874757Z digest=sha256:342b04129b17f07b76433bee726fa2c614cd1adce585cd1d88a9d4ec6d6de98c

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.

source=arxiv_source observed=2026-08-05T16:56:43.049524Z digest=sha256:4c400a16e415b348c4291f01f84bb16b54b1c4b541712fb73e3a1bee82e53455

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:43.174845Z digest=sha256:284248c3ed5fe6033603b3bf1ab7dfaec7a2126cedfed2f89d6e14b162d03ed1

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:43.257838Z digest=sha256:5941ecc9f4fdaa199c1bf99a7e01dd54fd6cf3969dfb06e252c1112757476df1

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:43.396049Z digest=sha256:40f312fb1377c1332a882c783bebbbb1adb4c15184e654fc0db68da89652c0ed

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:43.494392Z digest=sha256:05a151eb0261c07e8b5dbf3a2e31a183666c1bab46ab7844934da0a7d3310b8e

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:56:43.604758Z digest=sha256:ea386cd67c6bc02ead98a4e2fe309ba52efaa2fca8c906a97600cb43f8522868

Pith citing papers

No inbound Pith citation observations are available.