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Paper Citation Record · LEDGER

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework

As of 16 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 2 inbound Pith citation observations for arXiv:2412.12612.

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

pith.paper-citation-record.v1
2412.12612 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:59:58.270437Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T04:46:56.654470Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:36:45.352690Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact0
  • verified fuzzy22
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 082145f8-8d0a-438b-96f1-fdf46bbc8f6e · outbound

This paper cites Select Nodes and Relationships: Based on the query type, choose nodes and relationships to form the questions.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Select Nodes and Relationships: Based on the query type, choose nodes and relationships to form the questions

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.913396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.041617Z digest=sha256:2232c5eca362b1fa421b2086136301e2efbdb4eebea7f806d7ff3d2df7f0462e

Observation 153be6b0-f282-41e0-ade9-67d98362e448 · outbound

This paper cites Structure-Grounded Pretraining for Text-to-SQL.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Structure-Grounded Pretraining for Text-to-SQL

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-11T13:59:58.027688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:59:58.027688Z digest=sha256:82e774e32ec26048c3c4c9e1527e409bd1fbb348b2a4a972a75e2989f8af8dc5

Observation 661918ca-406e-4cce-84a6-2b41f2dcd00b · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.877844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.054919Z digest=sha256:a7a1a1071718df8ac3fcb830fb91f008554153761706c00a87812bf1fee93a63

Observation 1bdb5974-99e9-4685-92aa-90d700ea37e8 · outbound

This paper cites Random Selection: Randomly select nodes or relationships when forming each question, ensuring diversity in the coverage.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Random Selection: Randomly select nodes or relationships when forming each question, ensuring diversity in the coverage

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.862887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.067026Z digest=sha256:0ba91abc9519000ee316a83ae98a13c1a4f00c33638fc74a5ebc07d72f2d91c7

Observation f6444f36-1829-425e-8137-e9ab67bac9fc · outbound

This paper cites Ensure no two questions are similar.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Ensure no two questions are similar

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.894444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.048809Z digest=sha256:4ef921460c15fc6a5836f811ddb4c41e0b4e7972ca94b9a6bebbd84c860fd1af

Observation 85606155-d1c8-45de-bfe7-50ee9cc0d85c · outbound

This paper cites 1 million.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework 1 million

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.830071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.085141Z digest=sha256:6c705c889310391419b5193ffb8ba57a2e8e603e0987470b434c0b5142d5bb66

Observation c60e22b4-f2ce-4f3f-83eb-deb79df401b8 · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.713505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.142262Z digest=sha256:a6ac31dd3afd87c81bb86f0fecef32d13df017935c533483199277658dea9637

Observation 4873c0d9-9b81-4b82-9089-3c5505cfd9f4 · outbound

This paper cites 2024-01-01.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework 2024-01-01

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.845851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.076272Z digest=sha256:03741f18e1b0b245d59024366a273999b60cb8c2d0e227a73f2012f3510e0731

Observation 38466d9e-a96b-4e1f-81d1-00061ca5cc5b · outbound

This paper cites For example, if the question mentions 1 million, use 1000000; for 1.2 million, use 1200000.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework For example, if the question mentions 1 million, use 1000000; for 1.2 million, use 1200000

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.680644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.152765Z digest=sha256:ddb659881ba5b6d77e88d4921da53b51edece8ae5ba222340a2fa9aebab897d4

Observation af9154d4-5d3a-40a8-a950-acfa864653ba · outbound

This paper cites Understand which entities are crucial to construct the ground truth answer.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Understand which entities are crucial to construct the ground truth answer

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.814689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.093022Z digest=sha256:fed789f77b6447c2f9ac1a86011108ac415ddc0f475eed4350c5ea2432f5605d

Observation 984d1f7d-6322-47e4-b9e6-de28a6662fd0 · outbound

This paper cites Include both the ground truth data and additional negative data points.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Include both the ground truth data and additional negative data points

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.799163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.099420Z digest=sha256:e218ba8230e0467e817ac67f62bad491d6eb2c793faaa10209fab699ac828ae2

Observation 7e6a8c9a-cda7-405f-ba3a-1fb7cd180123 · outbound

This paper cites - Creating negative data points that do not match the answer but help ensure the test is comprehensive.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework - Creating negative data points that do not match the answer but help ensure the test is comprehensive

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.781601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.111204Z digest=sha256:725251739d912374c115d1be27602b7b9e6513e36d4f2702fe9a392e49a61aa6

Observation a9bad089-b221-430d-8e16-db00a1f5db77 · outbound

This paper cites Include details like names, summaries, and other fields, making sure the negative data does not overlap with the ground truth.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Include details like names, summaries, and other fields, making sure the negative data does not overlap with the ground truth

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.761914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.119290Z digest=sha256:c7addf67b00098d3ef3f10e39e656c4d85089b96cd44e44c6f9db74ca670b264

Observation 4ffbb228-3b65-4408-ba54-9111b0c7096c · outbound

This paper cites This ensures that the negative data is limited and doesn 't overwhelm the test case.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework This ensures that the negative data is limited and doesn 't overwhelm the test case

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.745387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.126012Z digest=sha256:beb708b1ed2a3c917a1f75d29e5298c2adeef7b3a46268632921e7bf09402499

Observation 4d277cb1-7869-4b20-b7c5-05b3fb9eaffb · outbound

This paper cites Specify which fields require unique values, using UUIDs or similar approaches.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Specify which fields require unique values, using UUIDs or similar approaches

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.729524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.135251Z digest=sha256:d71889f39cca610dbae9d3a6c773f53059ebd7e6a69ddbe9600235c0c5fb6682

Observation 8c2ab9d3-ee91-42ac-9950-c5cac8528266 · outbound

This paper cites Use the `MATCH` statement before creating relationships to ensure that the nodes exist and the correct connections are established.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Use the `MATCH` statement before creating relationships to ensure that the nodes exist and the correct connections are established

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.698096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.147710Z digest=sha256:e0c31b605f7f11d738f676ec7317fdd8e95e15b36e139eaf2add7e7b5162127b

Observation 3d80c064-f140-45d5-9088-52db7536a2b8 · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.661412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.158793Z digest=sha256:0f5b919b0dfb2aa2ee5dfdb9441b1e7ef083615e97e48b308cfefa792359a7f8

Observation a0abc45b-8a2b-46dd-b17c-138c617752aa · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.644717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.164168Z digest=sha256:f48b07d0684d33fadfe313c167f1a2d117eb2194d521073639da76041bd0ac97

Observation 017f2147-eae1-42f8-968d-56aafe75931e · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.628839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.169928Z digest=sha256:741b35a49963e3c6131b358af5e10ab23ce48d5112f6bcde58f4b835edca124e

Observation b54578fa-ef18-4708-b65a-bf341ca5d793 · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.612334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.174898Z digest=sha256:5e125ab94928a96c8ca44ffe2772c5b9b753e845eeef2474e1e89e8cedc961b6

Observation 80a97cc9-5766-4c6b-97a1-ece25b8a988e · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.596049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.183691Z digest=sha256:4dccaf0add009bf3d584577a723623a80255b58b5d0a36971a3d33b44584568c

Observation 84eb6335-7459-41e4-9897-a2afe6b2c4ab · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.579606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.197602Z digest=sha256:ff7638bf3d79140dac1288dc683aca37f595310f7aee0a90531ab6698acf7eb8

Observation a6beb4b2-27ec-445a-8077-f822d8b7e922 · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.563825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.204026Z digest=sha256:7730408e293602c49a535141f74189919731566a97bb63e78d3b7f8727684406

Observation 84502a4f-5f3a-4c1b-98d8-ee116f9aaf45 · outbound

This paper cites Ensure negative data points are not more than five.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Ensure negative data points are not more than five

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.547757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.212166Z digest=sha256:bf5ae1013054a126552dea816678cc919147720ef8304662744eb69b71a8cfee

Observation a9c62217-9de7-4407-9100-38a874a6e95d · outbound

This paper cites Code Writing Suggestions: - Avoid errors with f-strings by using string concatenation or `.format()` when needed.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Code Writing Suggestions: - Avoid errors with f-strings by using string concatenation or `.format()` when needed

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.529900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.217400Z digest=sha256:a3c1aeed8bbc722e560827b6d523eaa647e4c1ab01951977fecde551d76ef96c

Observation ad03d503-c7bf-4d88-9046-ff561f76e902 · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.514014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.223264Z digest=sha256:401e0e0c20e0711eb259c451bb2760bb36fcafa1832cf8a320a61e0a83fe6ef7

Observation 23f57384-3e24-47cb-bd85-fcae036ee916 · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.498386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.228716Z digest=sha256:2c571068164d595bbc4ffb0ee6075b551e4a4bd93a3c86a7e6a3269b7f099cb5

Observation 1ecf91b8-4d64-407b-8bcf-662ebed22397 · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.478740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.233558Z digest=sha256:f6e73f62a33a45f7552dab02257d57d2b0675923b89e5c9d45f115fd55b0b943

Observation c1e84d26-4c46-44af-9f50-c714ea3dfd65 · outbound

This paper cites an unresolved cited work.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:59:58.462186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.238330Z digest=sha256:480a8483456690e0d5d8c61ac96aa6dc14d36b064a9314a88a9d9d0808504f48

Observation abc1ab82-cf7c-45fa-8e0e-d225eca8465e · outbound

This paper cites - Understand what the user needs, keeping in mind the eventual answer.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework - Understand what the user needs, keeping in mind the eventual answer

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.443888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.243775Z digest=sha256:2595644d78bab339749b350c801aa5902aebe1d33fe29f496540f53cd481bdcc

Observation 7cbf7551-5ea5-4a29-90a1-7b1cd090c9d2 · outbound

This paper cites - Ensure that any indexes and constraints are considered when formulating your response.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework - Ensure that any indexes and constraints are considered when formulating your response

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.424342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.248893Z digest=sha256:092b2d4b833f7e7475db45b245648e117f28c2b87e3f04f11056cd9e188f2296

Observation fc567c6d-5128-407b-ba1e-cfece5b70791 · outbound

This paper cites Keep track of these nodes.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Keep track of these nodes

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.402982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.253885Z digest=sha256:89576bc498498182fc7cdf6690070f73abb9b8cd630c11e7b97f61b31553f868

Observation 04178fc5-3f44-42a4-8257-dd8443addfa6 · outbound

This paper cites Do not create imaginary relationships; only consider the relationships that are present in the schema.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Do not create imaginary relationships; only consider the relationships that are present in the schema

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.386371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.259460Z digest=sha256:ed0cf379d0e079456ba1abcb85643d6b0ccf34149ed9c90801f0c58ae7eac3b8

Observation 74cafca9-5b8b-4bd9-89ac-1060e13fc150 · outbound

This paper cites Do not create imaginary properties; only consider the properties that are present in the schema.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Do not create imaginary properties; only consider the properties that are present in the schema

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.370382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.264659Z digest=sha256:9d7d924f9651c28f62c917215c3a3e4935869aecf21cd18084493029ff1e3366

Observation a0ce65af-94db-47a8-acb1-c49a997e11f7 · outbound

This paper cites Cypher generation plan.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework Cypher generation plan

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.352621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.270437Z digest=sha256:40f9580916466aa89d028a38a833f54b4358e65f71160700ee7483d4b5bbe441

Observation ffdb34b6-a7be-4f8c-bd3a-707dd6ee7f37 · outbound

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

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework A Survey on Employing Large Language Models for Text-to-SQL Tasks

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-11T13:59:58.034914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:59:58.034914Z digest=sha256:bdafc486f4a4c51b401c2d1243e65f3aac705bb8eba66dd5c427e35d5faa27fb

Observation 2ac35a1b-f433-4722-b0b5-ef2845c771e6 · outbound

This paper cites https://huggingface.co/datasets/ tomasonjo/text2cypher-gpt4o-clean?row=0.

Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework https://huggingface.co/datasets/ tomasonjo/text2cypher-gpt4o-clean?row=0

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:59:58.931149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T13:59:58.020326Z digest=sha256:12e0a4e8262c2bc61fb5408557c14ac0355b9c096567d175db7eb99646da1010

Pith citing papers

Observation a123a844-39d9-43aa-aec0-1ff43c107562 · inbound

CYGNET: Cypher Gate for Neural Execution Triage and Cost Containment cites this paper.

CYGNET: Cypher Gate for Neural Execution Triage and Cost Containment Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-07-02T07:36:45.354515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-28T06:49:23.432383Z digest=sha256:bfe0a48268a3816764d38279d5e0048b586e1b31a39a0fcbb013c70b28922fc1

Observation 9bb09f7c-1d18-4ac3-b690-f5ba416c8a6b · inbound

KG2Cypher: Data-Centric Pipeline for Building Enterprise Text-to-Cypher Systems cites this paper.

KG2Cypher: Data-Centric Pipeline for Building Enterprise Text-to-Cypher Systems Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T19:13:53.471761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-29T04:46:56.654470Z digest=sha256:925fb7db0f6b37dc277a137cb6b685a79a2e5764c3157940e76d63a8198a8b03