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Paper Citation Record · LEDGER

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval

As of 20 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2607.13311.

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

pith.paper-citation-record.v1
2607.13311 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T05:38:05.945559Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b97c48a2-1b0b-4c61-800b-11cbc25b00ed · outbound

This paper cites an unresolved cited work.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval Unresolved cited work

Reference 9

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unresolved
no resolver link, observed 2026-08-02T05:38:05.385914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:05.385914Z digest=sha256:25ff20a75f5e10faba5e5919ecfcb0f50c89d2b1f7a2ff2e53a22c5b65f33324

Observation 7cca6b27-ae8e-46cd-bb03-f18255b5e128 · outbound

This paper cites https://github.com/bird- bench/livesqlbench.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval https://github.com/bird- bench/livesqlbench

Reference 10

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unresolved
no resolver link, observed 2026-08-02T05:38:05.487691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:05.487691Z digest=sha256:0a06b9e7e34b4635b8e514b8c11653bc579c30b3f312b92a887efb8e11e0a4b3

Observation a6403739-2376-4f5c-ae14-35090870a4e0 · outbound

This paper cites an unresolved cited work.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval Unresolved cited work

Reference 11

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unresolved
no resolver link, observed 2026-08-02T05:38:05.612402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:05.612402Z digest=sha256:b96f95bdbbf11666155be9f347843a43dbd115bdc3dd959a71565fe2e8b43f5b

Observation 20973b10-dad6-43f0-83df-dbdce53ccdf6 · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 12

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unresolved
no resolver link, observed 2026-08-02T05:38:05.736898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:05.736898Z digest=sha256:d54b1424d38e45ce09ea9378e93b961b2c60aea2bd121287dc886e3437073ce1

Observation 91db9932-639d-42d0-90b9-31cf829bb559 · outbound

This paper cites Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-02T05:38:05.814131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:05.814131Z digest=sha256:f105fca8b97e93a589b8352663b374776c858cc0cd587e782611448ea6303d8c

Observation 18ed0219-7eec-4942-ab63-180d579b4f99 · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 15

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unresolved
no resolver link, observed 2026-08-02T05:38:05.904886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:05.904886Z digest=sha256:9f2b81efbfa22ca0b14fb46aaeb3115050f996cb92ca085a98166e9f25c8debf

Observation 03037b5a-949b-493c-9915-ee88d6083760 · outbound

This paper cites Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 2017

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unresolved
no resolver link, observed 2026-08-02T05:38:05.945559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:05.945559Z digest=sha256:670d2577ef64b259785da3bd08891dd5365e5c947aa8f3cbc991d62122eb1a5d

Observation 8fa2e5c8-7c6c-4631-b9dd-30e964d64e9b · outbound

This paper cites InProceedings of the 2018 Conference on Empirical Methods in Natural Lan- guage Processing, pages 3911–3921, Brussels, Bel- gium.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval InProceedings of the 2018 Conference on Empirical Methods in Natural Lan- guage Processing, pages 3911–3921, Brussels, Bel- gium

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-02T05:38:05.866302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:05.866302Z digest=sha256:a4b54ed9435403211f45e9bf4bd874b25c50f0a52d37b51df3f88083784ea821

Observation 3160c85f-7f22-492d-b237-ba29d3c34e23 · outbound

This paper cites Document Expansion by Query Prediction.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval Document Expansion by Query Prediction

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-02T05:38:05.182424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:05.182424Z digest=sha256:c94d6a26c4bcda0742b0147d6ba5c6d0e397401793c1bb3de87a781b12345926

Observation 65b415a1-9783-4e60-b0c3-ece85eb959c4 · outbound

This paper cites InProceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769–6781, Online.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval InProceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769–6781, Online

Reference 2020

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unresolved
no resolver link, observed 2026-08-02T05:38:04.484088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a2ca9db2-b0db-4756-ac2d-5693ca967bff · outbound

This paper cites InProceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Hu- man Language Technologies, pages 5835–5847, On- line.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval InProceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Hu- man Language Technologies, pages 5835–5847, On- line

Reference 2021

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unresolved
no resolver link, observed 2026-08-02T05:38:05.279799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:05.279799Z digest=sha256:5d8acdb1a5fef2289a3306872e048099adf6663d3aa05fb8376bf5169e92c28f

Observation 20443763-e8d5-4780-9904-8976e1d8cff8 · outbound

This paper cites Promptagator: Few-shot Dense Retrieval From 8 Examples.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval Promptagator: Few-shot Dense Retrieval From 8 Examples

Reference 2022

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unresolved
no resolver link, observed 2026-08-02T05:38:04.339592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:04.339592Z digest=sha256:2ba106f6ccf35b8e8ac95a5aa48641845e4b08bef940b277567d1be02a3a3ce5

Observation 2b2cdd30-afb7-491d-b635-210891d22f95 · outbound

This paper cites InProceedings of the 17th Conference of the European Chapter of the Association for Com- putational Linguistics, pages 2014–2037, Dubrovnik, Croatia.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval InProceedings of the 17th Conference of the European Chapter of the Association for Com- putational Linguistics, pages 2014–2037, Dubrovnik, Croatia

Reference 2023

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unresolved
no resolver link, observed 2026-08-02T05:38:05.017323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:05.017323Z digest=sha256:7227d030cde2dd510f5a51f45c0f56e752b4010d86fda1d38e23ef3703b52577

Observation 8306f99a-2e4a-47ba-9cec-5bca3c7661f1 · outbound

This paper cites Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 2024

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unresolved
no resolver link, observed 2026-08-02T05:38:04.815422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:04.815422Z digest=sha256:00355fb87335c20c7c9a9e4b8459f174dee10bbb1a27168c55b3ea162e6b3fe7

Observation 79d1500f-94e3-4de7-ad4c-355582051aed · outbound

This paper cites CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval

Reference 2025

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no resolver link, observed 2026-08-02T05:38:04.668615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:38:04.668615Z digest=sha256:d78242b0b849bc806a8cd351954e8f7397fabee6ecae2c509b799d6300cbbdd4

Observation e6389750-bf39-487e-9f4d-d90c35597b9b · outbound

This paper cites BEAVER: An Enterprise Benchmark for Text-to-SQL.

Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval BEAVER: An Enterprise Benchmark for Text-to-SQL

Reference 2026

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no resolver link, observed 2026-08-02T05:38:04.253210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.