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Paper Citation Record · LEDGER

Aligning Large Language Models to a Domain-specific Graph Database for NL2GQL

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.16567.

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

pith.paper-citation-record.v1
2402.16567 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 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:10:13.365952Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T05:51:10.628789Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 051648b7-9d5c-4d0f-96c1-3d991bfbe512 · inbound

FathomGPT: A Natural Language Interface for Interactively Exploring Ocean Science Data cites this paper.

FathomGPT: A Natural Language Interface for Interactively Exploring Ocean Science Data Aligning Large Language Models to a Domain-specific Graph Database for NL2GQL

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-11T23:10:13.365952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:10:13.365952Z digest=sha256:48b7eba21fecac4d043970c5c1a24a583f4ab66228827117a286e7554ecf81b5

Observation ca58eaf4-aa75-472a-9f14-d15095649541 · inbound

A Collaborative Multi-Agent Approach to Retrieval-Augmented Generation Across Diverse Data cites this paper.

A Collaborative Multi-Agent Approach to Retrieval-Augmented Generation Across Diverse Data Aligning Large Language Models to a Domain-specific Graph Database for NL2GQL

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-11T20:19:02.122415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:19:02.122415Z digest=sha256:7cc4f225553324d46263a997ece1aea0b7134c9a56a2daed596d0a24185be724

Observation d2e22928-8c12-424a-845f-ded753f0d491 · inbound

CypherBench: Towards Precise Retrieval over Full-scale Modern Knowledge Graphs in the LLM Era cites this paper.

CypherBench: Towards Precise Retrieval over Full-scale Modern Knowledge Graphs in the LLM Era Aligning Large Language Models to a Domain-specific Graph Database for NL2GQL

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-11T04:36:19.933447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:36:19.933447Z digest=sha256:db55d67ec0840a44f82ad703200013a5a3ba5139ccbfccab2f1fd246ca773f1e

Observation d100d541-e26b-4f50-a2c4-aadb0c916cd5 · inbound

Synergizing Logical Reasoning, Knowledge Management and Collaboration in Multi-Agent LLM System cites this paper.

Synergizing Logical Reasoning, Knowledge Management and Collaboration in Multi-Agent LLM System Aligning Large Language Models to a Domain-specific Graph Database for NL2GQL

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T20:39:04.741526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:39:04.741526Z digest=sha256:8f01f4336a710b0bbd0b176ad61d95c2b61586ece00ccf5e01c623e4c383b8e9

Observation 8c81a462-1c9b-4dd4-8bc6-6281ea07d6ee · inbound

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval cites this paper.

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval Aligning Large Language Models to a Domain-specific Graph Database for NL2GQL

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:51:10.630060Z

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.

source=arxiv_source observed=2026-05-10T05:43:04.813867Z digest=sha256:27b034a749e0bfb6c5b2d0919afc38db36057466d6488102a4f888abf6b2fe9d