Paper Citation Record · LEDGER

Balancing Content Size in RAG-Text2SQL System

As of 14 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 1 inbound Pith citation observation for arXiv:2502.15723.

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

pith.paper-citation-record.v1
2502.15723 v3

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T11:12:28.989069Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T07:28:32.185178Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T13:48:21.394678Z

Reference resolution

27 of 27 outbound references displayed

verified exact1
verified fuzzy2
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c2dc3d3d-92d8-47f8-bdd8-7ad5a48e9425 · outbound

This paper cites A Survey on Employing Large Language Models for Text-to-SQL Tasks.

Balancing Content Size in RAG-Text2SQL System A Survey on Employing Large Language Models for Text-to-SQL Tasks

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.835243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eaf6052f-1d8c-4f5b-a1c2-bd1acf3f2ce6 · outbound

This paper cites Improving language models by retrieving from trillions of tokens.

Balancing Content Size in RAG-Text2SQL System Improving language models by retrieving from trillions of tokens

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.853475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15cb1aba-032e-4a31-adcb-a88cf4812ad5 · outbound

This paper cites A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications.

Balancing Content Size in RAG-Text2SQL System A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.865017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec35c364-ecb8-402f-9f8c-6f8adb7a59e4 · outbound

This paper cites Efficient Prompting Methods for Large Language Models: A Survey.

Balancing Content Size in RAG-Text2SQL System Efficient Prompting Methods for Large Language Models: A Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.870841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5134fb03-fba2-4209-843e-7a6a0f918ba4 · outbound

This paper cites Evaluating Verifiability in Generative Search Engines.

Balancing Content Size in RAG-Text2SQL System Evaluating Verifiability in Generative Search Engines

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.876851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 401da26c-f6c2-41c4-9a3a-5a50691ea969 · outbound

This paper cites Influence of External Information on Large Language Models Mirrors Social Cognitive Patterns.

Balancing Content Size in RAG-Text2SQL System Influence of External Information on Large Language Models Mirrors Social Cognitive Patterns

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.887933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0cfd53b-8e24-450a-a1b3-03850e9301a7 · outbound

This paper cites Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering.

Balancing Content Size in RAG-Text2SQL System Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.894739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45ce9ad0-1fc9-4e29-afb2-36ec6eedc8ab · outbound

This paper cites Text2SQL is Not Enough: Unifying AI and Databases with TAG.

Balancing Content Size in RAG-Text2SQL System Text2SQL is Not Enough: Unifying AI and Databases with TAG

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.900522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46e205f2-b69e-4815-b837-2371caca87a8 · outbound

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

Balancing Content Size in RAG-Text2SQL System Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.906238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75df18a8-ea96-4c41-bde2-30fdc4b408eb · outbound

This paper cites Understanding the Fundamental Design Decisions of Retrieval-Augmented Generation Systems.

Balancing Content Size in RAG-Text2SQL System Understanding the Fundamental Design Decisions of Retrieval-Augmented Generation Systems

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.919327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 760e7f57-1364-4e1b-8cb7-943b8134d887 · outbound

This paper cites Language Models are Few-Shot Learners.

Balancing Content Size in RAG-Text2SQL System Language Models are Few-Shot Learners

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.924992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 430eb28e-e89c-4c9a-8488-9847514de60f · outbound

This paper cites Large Language Models are Zero-Shot Reasoners.

Balancing Content Size in RAG-Text2SQL System Large Language Models are Zero-Shot Reasoners

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.933300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 328365f6-2117-4573-b883-4f41aae9fc4b · outbound

This paper cites Question-Analysis Prompting Improves LLM Performance in Reasoning Tasks.

Balancing Content Size in RAG-Text2SQL System Question-Analysis Prompting Improves LLM Performance in Reasoning Tasks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.939675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9365fb59-0307-4643-82a5-52e408a79b96 · outbound

This paper cites Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback.

Balancing Content Size in RAG-Text2SQL System Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.944984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83721edf-cec4-45c8-8999-28e3b9b3c573 · outbound

This paper cites Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Grounding.

Balancing Content Size in RAG-Text2SQL System Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Grounding

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.950210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28da4de5-c8ed-410a-8c0a-91f3fabf7784 · outbound

This paper cites A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation.

Balancing Content Size in RAG-Text2SQL System A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.960669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation beb2573f-1df8-4f37-bd49-432a0b10ffdb · outbound

This paper cites Chain-of-Verification Reduces Hallucination in Large Language Models.

Balancing Content Size in RAG-Text2SQL System Chain-of-Verification Reduces Hallucination in Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.967765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 332559d2-bd47-48cb-b75e-2fa1bab89614 · outbound

This paper cites Cunningham, and David Blei.

Balancing Content Size in RAG-Text2SQL System Cunningham, and David Blei

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.973021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9aadd56b-8663-4901-866d-42019bd43ee9 · outbound

This paper cites Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task.

Balancing Content Size in RAG-Text2SQL System Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.978303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0448d1c5-c502-47d5-bdd2-b57a699bf3a1 · outbound

This paper cites The Faiss library.

Balancing Content Size in RAG-Text2SQL System The Faiss library

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.989069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8015aacb-811a-4a03-b831-57d4d0dc332d · outbound

This paper cites Observations on Building RAG Systems for Technical Documents.

Balancing Content Size in RAG-Text2SQL System Observations on Building RAG Systems for Technical Documents

Reference 2017

Resolution: verified exact; local_arxiv, observed 2026-08-10T11:12:29.505971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 34169c70-ca95-47c0-a9b0-b4e28c55ce50 · outbound

This paper cites Retrieval-Augmented Generation for AI-Generated Content: A Survey.

Balancing Content Size in RAG-Text2SQL System Retrieval-Augmented Generation for AI-Generated Content: A Survey

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.983081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80649380-b7b6-4a9e-94a0-dc3dfbf00b47 · outbound

This paper cites Atlas: Few-shot Learning with Retrieval Augmented Language Models.

Balancing Content Size in RAG-Text2SQL System Atlas: Few-shot Learning with Retrieval Augmented Language Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.847952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dfcd688-709b-4383-be50-00ad48874003 · outbound

This paper cites Trapping LLM Hallucinations Using Tagged Context Prompts.

Balancing Content Size in RAG-Text2SQL System Trapping LLM Hallucinations Using Tagged Context Prompts

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.955456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6875f295-f8bf-4418-8b19-6b0d3a182a6d · outbound

This paper cites Searching for best practices in retrieval-augmented generation.

Balancing Content Size in RAG-Text2SQL System Searching for best practices in retrieval-augmented generation

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:12:29.756010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c7489f43-701e-4b0e-9611-75677972d356 · outbound

This paper cites On faithfulness and factuality in abstractive summarization.

Balancing Content Size in RAG-Text2SQL System On faithfulness and factuality in abstractive summarization

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:12:29.735019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8673652c-dbc7-4664-b84b-70b55f583f99 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Balancing Content Size in RAG-Text2SQL System Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T11:12:28.841490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 91ef1956-c446-4c6c-8710-928fd97b0845 · inbound

TAHOE: Text-to-SQL with Automated Hint Optimization from Experience cites this paper.

TAHOE: Text-to-SQL with Automated Hint Optimization from Experience Balancing Content Size in RAG-Text2SQL System

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-03T13:48:21.396545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.