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Paper Citation Record · LEDGER

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

As of 15 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 2026-08-15T06:32:42.880941+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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.041617Z digest=sha256:642889b449113075cd92e88291ba633889d3ac0106c8e09ff757f5c64eb65a99

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.054919Z digest=sha256:6fe02ed8d3dff1a795d3f5d4e854fcb7b021ea899699c456e40b861e2f2dbffe

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.067026Z digest=sha256:5dfb1c7c0b8ad301b9081492f9de8eef4c80a3d4170f1208ea6dec12764bd20b

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.048809Z digest=sha256:9204240434be3166e58ff0e1f06624872b4bbddd425d41a4dddd029987789fdf

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.085141Z digest=sha256:53830c4e7307e7035bb04d242f42b41182f9fe39cbc93f130963c94d3ab828e6

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.142262Z digest=sha256:d57ebf3257dc74d313206c6046a446606036ba8ffd0e7d090e10105805459278

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.076272Z digest=sha256:79f3915a68f7088d80c091e3223330fe40a47a25a92706a1c5464365c95c43f2

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.152765Z digest=sha256:7cd229d654ba0178dfd2f121781a4bff85b63ac79869d6db04e81fe34b45785f

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.093022Z digest=sha256:61fabc04da13b39a1772a62bf771da4732a71c1d69fee1883af305ec6bfc388a

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.099420Z digest=sha256:929a122cb4f4f548dc544e2612b2a9fc97ca4246683613ca638fbadf2339780d

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.111204Z digest=sha256:38f9790c07f8ed58b84f63867c0f87aa8d713b408d7907f3339967c8f90962b7

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.119290Z digest=sha256:98ad7bbec6d146c3d827281534969eadae0d5ad5ae869e6593047bcaa3027d25

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.126012Z digest=sha256:4b3503f37fd9ce68bbe5a00d50693d0bd73bd42ff266a7a33e65b1c46ef84340

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.135251Z digest=sha256:12213105a1a5351eb4a4415ae7c98fd47e6e4c8c2bf31110aaa467e26f3cb051

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.147710Z digest=sha256:6649a012b67a2dcee771bbdde420e4eddd72aabd0821dcfcdde0e682bdf2c97d

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.158793Z digest=sha256:b7a12e33468133342bc9ab27fe4a56dbc5547aef107135edfdc7e9983b5dd83e

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.164168Z digest=sha256:90b7070aa6733c6b50a6cfc15c49515f4aa5ebab4ed2c2673bc8ad6a5e9743fd

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.169928Z digest=sha256:7b397171672928a74081228715ef5ee7b2f78868477eab5e6ff494556db190dd

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.174898Z digest=sha256:890b038bbb3804710c788bfabf68120b5d4a4d1e9353404810f9ae8ead0c3b65

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.183691Z digest=sha256:0962dc603dbd2545a3b128cefd709d3e4aad3d7a58e8009f303b7acf125cb143

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.197602Z digest=sha256:e3d58f69a2e3159eec1a79e0d1944be24fbb3f0c694c19cae725edc11c1ff755

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.204026Z digest=sha256:9d091a5e4b88a218fba9a7cc107aceee340e9cb4bfec26bd66ed3554dfbd1f71

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.212166Z digest=sha256:5d84948979d2797e7a9e9b1b2eaec9286f5036483b373d0a598db376b7558603

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.217400Z digest=sha256:d62f8d350a4fb5a5c047096c434cb3fa05ad838968e6f81d784212689f23c882

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.223264Z digest=sha256:d1757d9d1779e5fb22653373f5d1d44220decc727d715e49695215695f844a78

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.228716Z digest=sha256:dbbddcdedef0fb3b0a6e1040065aa0bb4f86b49c4e4673ec4c9db2d4a9754b4f

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.233558Z digest=sha256:3137f67c6603d5e352e3031a79546a08d777d6b08ea7519d7e0538190a3988b1

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.238330Z digest=sha256:f496010e62f3591e9ca6ef9191f258506549e3d065f2fb28361b4df2592ada2d

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.243775Z digest=sha256:4d59cf468f55d1b66e31da67847c8a842c5c0d464d053f1546bb7b0cc62990a5

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.248893Z digest=sha256:20f3070e66c1af7117e0bd348751d87af199413e98291d0a03f3adaa5fa3347f

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.253885Z digest=sha256:f4d4f9064eeca7546e58b4aeb49bb687fc916367740dfd29459c347d1e8f6bf9

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.259460Z digest=sha256:ab8992773dfe9bb1173958a7834bfe2d538b8d4ed538baa611a4f9182bfad249

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.264659Z digest=sha256:ceff75b290773549abf9f024bb5c4d5a16eaff84861c25351689e8115199aa26

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.270437Z digest=sha256:86455c827bf72afd92fd29cd934817abfc7f336738d3b8287304c6a3d6dc7a71

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T13:59:58.020326Z digest=sha256:6423e93ca62b80fd34150049c10eb98dc47e0d55fe490e06b53fc8cef8fff064

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T06:49:23.432383Z digest=sha256:7a448b60fc0b9c96c74fbd1b84ac49bfb1d8f15096d4374692103a92e7bea593

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-29T04:46:56.654470Z digest=sha256:ac3f519a65ca43620f4983dc0ccf991c6df20957c39403986e45b5ee38b5f93d