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Paper Citation Record · LEDGER

Grammar Prompting for Domain-Specific Language Generation with Large Language Models

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.19234.

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

pith.paper-citation-record.v1
2305.19234 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:36:45.590581Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

24
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 40826b50-9319-4c3b-a29a-b484ea51fad4 · inbound

XGrammar: Flexible and Efficient Structured Generation Engine for Large Language Models cites this paper.

XGrammar: Flexible and Efficient Structured Generation Engine for Large Language Models Grammar Prompting for Domain-Specific Language Generation with Large Language Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T14:36:45.590581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:36:45.590581Z digest=sha256:a19c8405052f82a77e48a67cffa44732d225cd84c47cf5e9362b58f59a9da9b3

Observation d54ad833-e6fc-4a3b-91e4-97a14b128ae8 · inbound

XGrammar-2: Dynamic and Efficient Structured Generation Engine for Agentic LLMs cites this paper.

XGrammar-2: Dynamic and Efficient Structured Generation Engine for Agentic LLMs Grammar Prompting for Domain-Specific Language Generation with Large Language Models

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-03T12:07:34.077691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T12:07:34.077691Z digest=sha256:aef56cda0f72bc84b007cea1c8e8995112efebef1e457ed97a387b89e0cf6e24

Observation 311eebf2-523e-4a50-b457-d5c5e45a8ad8 · inbound

Context-Instrumental Data Distillation for Kubernetes Manifest Generation: Method and Experimental Evaluation cites this paper.

Context-Instrumental Data Distillation for Kubernetes Manifest Generation: Method and Experimental Evaluation Grammar Prompting for Domain-Specific Language Generation with Large Language Models

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T23:14:00.940898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-29T23:07:08.124993Z digest=sha256:951dddbb7537fc3c264109824b4c3174e2e29248fe893e0a0fa62b0375462e32

Observation c6443306-94ae-48b9-8346-3594f6f43d4c · inbound

Sequential Planning via Anchored Robotic Keypoints cites this paper.

Sequential Planning via Anchored Robotic Keypoints Grammar Prompting for Domain-Specific Language Generation with Large Language Models

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-06-30T05:04:20.345871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T04:59:12.363425Z digest=sha256:df0b8b2b42f9b5b809268ec8f9cf026c984f72118c7776e854750572ad1d3d94

Observation 5d5903cf-34ab-4765-b5ea-04d50d6eba97 · inbound

ASMR: Agentic Schema Generation for Ship Maintenance Report Writing cites this paper.

ASMR: Agentic Schema Generation for Ship Maintenance Report Writing Grammar Prompting for Domain-Specific Language Generation with Large Language Models

Reference 19

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T11:57:03.402578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-10T11:50:21.908637Z digest=sha256:db5256d31940c0834388d6fcf1b346ee3d303289cacd550a346ebff4a7b7b24a