Paper Citation Record · LEDGER

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking

As of 15 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2412.05561.

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

pith.paper-citation-record.v1
2412.05561 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:39:47.287767Z

measured 47 of 47 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 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

47 of 47 outbound references displayed

verified exact2
verified fuzzy20
unresolved25
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 607df432-45bd-489a-85cc-2b8650213a2a · outbound

This paper cites write newline.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.022210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32e9d047-7cea-47fe-85c4-fc49a1b96f15 · outbound

This paper cites F oundations of D atabases: T he L ogical L evel.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking F oundations of D atabases: T he L ogical L evel

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.333474Z

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 5b3cc97b-10d6-4e46-ab6d-a11e70201b16 · outbound

This paper cites Sym KGQA : Few-shot knowledge graph question answering via symbolic program generation and execution.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Sym KGQA : Few-shot knowledge graph question answering via symbolic program generation and execution

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.315752Z

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 b1b51836-de14-449d-b04d-20853ef21a16 · outbound

This paper cites Exploring Large Language Models for Code Explanation.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Exploring Large Language Models for Code Explanation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.040654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0963c96-e4af-4f70-8df5-59b9d238a1b4 · outbound

This paper cites Language Models are Few-Shot Learners.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Language Models are Few-Shot Learners

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.051572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67d5a79a-1d32-465c-a4b9-d04ee48e0519 · outbound

This paper cites SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.056774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08fc0b58-53f7-4353-9141-e2991ee8cf4c · outbound

This paper cites Calcite Test Suite , 2021.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Calcite Test Suite , 2021

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.298934Z

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 793690a9-56f2-4777-a062-5ec5e73cec5b · outbound

This paper cites Chandra and Philip M.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Chandra and Philip M

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.281172Z

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 374a238e-bde1-426c-aff4-3dc643a063bb · outbound

This paper cites an unresolved cited work.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-11T20:39:48.264725Z

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 43b0c497-9414-485e-803e-bd8f2b50bd63 · outbound

This paper cites an unresolved cited work.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-11T20:39:48.248037Z

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 abdf52d3-6175-4c5f-aa35-1ca25557cf37 · outbound

This paper cites Conjunctive query containment revisited.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Conjunctive query containment revisited

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.231681Z

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 d95f247b-33d3-45e5-95a1-e68724aa84d7 · outbound

This paper cites Hottsql: proving query rewrites with univalent sql semantics.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Hottsql: proving query rewrites with univalent sql semantics

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.214245Z

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 8e5e57e1-7071-4322-88cd-ecca079460b3 · outbound

This paper cites Cosette: An A utomated P rover for SQL.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Cosette: An A utomated P rover for SQL

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.196180Z

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 9565d66d-088e-4ea8-94cc-74494a689b56 · outbound

This paper cites Axiomatic foundations and algorithms for deciding semantic equivalences of SQL queries.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Axiomatic foundations and algorithms for deciding semantic equivalences of SQL queries

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.099051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23ff55b3-5751-4fb1-bd8d-4766b6a3429e · outbound

This paper cites Equivalence of queries combining set and bag-set semantics.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Equivalence of queries combining set and bag-set semantics

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.178714Z

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 7ea3ff45-a061-4209-833a-5e013be16fba · outbound

This paper cites P roving Q uery E quivalence U sing L inear I nteger A rithmetic.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking P roving Q uery E quivalence U sing L inear I nteger A rithmetic

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.160612Z

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 1cdc6275-4938-4855-b123-dd256e05eb76 · outbound

This paper cites Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.117182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34d289b6-a729-4828-a5be-04f3c0316eda · outbound

This paper cites an unresolved cited work.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-11T20:39:48.141599Z

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 b7ef3ecf-4d73-40d6-b8cd-1f02291fc221 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Gemini: A Family of Highly Capable Multimodal Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.129196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca388ce8-26d2-4f97-9e66-be19fda25ce6 · outbound

This paper cites Large language models are few-shot summarizers: Multi-intent comment generation via in-context learning.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Large language models are few-shot summarizers: Multi-intent comment generation via in-context learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.123375Z

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 8716a5a8-7ba0-45f1-92a5-b9e849fdfc1e · outbound

This paper cites GE q O : ML - A ccelerated S emantic E quivalence D etection.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking GE q O : ML - A ccelerated S emantic E quivalence D etection

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.107170Z

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 208cc48e-e81f-4b0c-b2c3-df0253167613 · outbound

This paper cites VeriEQL: Bounded Equivalence Verification for Complex SQL Queries with Integrity Constraints.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking VeriEQL: Bounded Equivalence Verification for Complex SQL Queries with Integrity Constraints

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-11T20:39:47.734209Z

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 0938ec6d-ab5f-44c6-b27a-c0e04518c44b · outbound

This paper cites Ioannidis and Raghu Ramakrishnan.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Ioannidis and Raghu Ramakrishnan

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.090347Z

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 acd88edf-b86a-4b25-b297-b598c57d02e3 · outbound

This paper cites Query optimization in database systems.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Query optimization in database systems

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.158036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e188ac71-4e34-45b8-8971-31d75dc0bbe5 · outbound

This paper cites Johnson and Anthony C.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Johnson and Anthony C

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.073320Z

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 169387f7-4471-49e2-a4ff-5d023d10b02c · outbound

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

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Large Language Models are Zero-Shot Reasoners

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.168506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9919bc6d-a7a4-4cf4-a488-7dac39e7fda0 · outbound

This paper cites A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.177664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49daab1f-389a-4001-ba01-e4bdfaec987a · outbound

This paper cites G-eval: Nlg evaluation using gpt-4 with better human alignment.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking G-eval: Nlg evaluation using gpt-4 with better human alignment

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.056537Z

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 2f93514a-2012-4e70-9db4-97316e3c1ef7 · outbound

This paper cites R eview: B.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking R eview: B

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.037507Z

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 322c0802-ea30-43c8-93d4-069aca56f9ad · outbound

This paper cites GPT-4 Technical Report.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking GPT-4 Technical Report

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.193148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da5cb6eb-1f49-4f4c-9cd0-f378b317534b · outbound

This paper cites DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.199667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7641527f-f08e-4d3b-bbe9-21ad16ebaa32 · outbound

This paper cites RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.205346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dd8c059-87ef-433d-81fb-be974f8a6b7e · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Code Llama: Open Foundation Models for Code

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.211726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62a0f259-9d14-474f-9b2e-bb0abe22b46f · outbound

This paper cites A Prompt Learning Framework for Source Code Summarization.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking A Prompt Learning Framework for Source Code Summarization

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.217650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bbfd983-2bf6-46aa-993f-73ba4f4774f8 · outbound

This paper cites T owards P ractical SQL E quivalence R easoning.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking T owards P ractical SQL E quivalence R easoning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:48.017129Z

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 7cf04a7d-a1c6-44b2-a954-4d6a8312743a · outbound

This paper cites We T une: A utomatic D iscovery and V erification of Q uery R ewrite R ules.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking We T une: A utomatic D iscovery and V erification of Q uery R ewrite R ules

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:47.997709Z

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 4d3cc782-ca32-458e-ba0a-34337ee24632 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.233608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27513089-0aaa-4ef7-82a6-a1185e1ba10a · outbound

This paper cites UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.238560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32f2c176-29df-4132-aded-d15157e758a9 · outbound

This paper cites TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.243698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbbcbd18-a2c6-475d-b336-e5768988fb79 · outbound

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

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.248574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a69c267-8b96-4dbd-a5be-376f709cb635 · outbound

This paper cites LLM-SQL-Solver: Can LLMs Determine SQL Equivalence?.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking LLM-SQL-Solver: Can LLMs Determine SQL Equivalence?

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.253223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 836f05f0-2f5c-4236-8f97-a6a203625d66 · outbound

This paper cites Semantic evaluation for text-to-sql with distilled test suite.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Semantic evaluation for text-to-sql with distilled test suite

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:47.979922Z

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 df1a60da-db59-47d1-a39a-2e34ffe6af88 · outbound

This paper cites Navathe, William R.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Navathe, William R

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:47.960820Z

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 0e2fbcc8-1f11-4889-8a73-1f9925bb9887 · outbound

This paper cites Navathe, William Harris, and Jinpeng Wu.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Navathe, William Harris, and Jinpeng Wu

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:39:47.943023Z

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 7c2fb4c5-661c-4aec-a1bf-a6f5dedad9f6 · outbound

This paper cites @esa (Ref.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking @esa (Ref

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.275633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c23f137-416c-491c-bde9-a4cff292381c · outbound

This paper cites an unresolved cited work.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Unresolved cited work

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T20:39:47.281297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 858f822b-a93d-474e-98a6-774c5f5ba159 · outbound

This paper cites Batting" -- Columns:.

Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking Batting" -- Columns:

Reference 48

Resolution: verified exact; raw_fallback, observed 2026-08-11T20:39:47.407214Z

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.

Pith citing papers

No inbound Pith citation observations are available.