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Paper Citation Record · LEDGER

Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2306.11489.

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

pith.paper-citation-record.v1
2306.11489 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:16:36.666495Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, 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

27
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a621102b-5b3a-44d4-b485-5543006f219f · inbound

K-ON: Stacking Knowledge On the Head Layer of Large Language Model cites this paper.

K-ON: Stacking Knowledge On the Head Layer of Large Language Model Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-08T16:16:36.666495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:16:36.666495Z digest=sha256:913a9785975b999ca3b296fd09e3196628e553a089c1d6a10a102e09a833d2a3

Observation 38a951d8-d033-418b-85a9-3b6739997231 · inbound

Large Language Model-Driven Distributed Integrated Multimodal Sensing and Semantic Communications cites this paper.

Large Language Model-Driven Distributed Integrated Multimodal Sensing and Semantic Communications Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:21.746652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:21.746652Z digest=sha256:b1272daae5cd411a5569afe90d2379495f61be7dd28af0a6d1cb1dce40c00476

Observation ab61b89d-38be-4dbe-bfb4-69d6815c2662 · inbound

FinRipple: Aligning Large Language Models with Financial Market for Event Ripple Effect Awareness cites this paper.

FinRipple: Aligning Large Language Models with Financial Market for Event Ripple Effect Awareness Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T13:24:42.217643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:24:42.217643Z digest=sha256:677bdb29ae60f727aadf020548a58d474baf84a58a83761202c2a87bc0721b73

Observation 47510307-b143-4914-a1ef-d7f1108ffa55 · inbound

Graph Repairs with Large Language Models: An Empirical Study cites this paper.

Graph Repairs with Large Language Models: An Empirical Study Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T20:19:44.275987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:19:44.275987Z digest=sha256:2c694ed6c00ea898f6a1c2e86dd60068dcf7f5ec765e51557cbed844e448a693

Observation 6f0f03bc-3966-4adf-b3ed-aea4eb7e1786 · 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 Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:56:11.481132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T05:43:04.813867Z digest=sha256:4fe7f6b54271e78f9f776dce4d546292748213f3c4c38d6a284a0cf16fcc73c6

Observation bfa7886b-dba0-47a5-8e19-d0dacf775ced · inbound

APT-Agent: Automated Penetration Testing using Large Language Models cites this paper.

APT-Agent: Automated Penetration Testing using Large Language Models Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling

Reference 21

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T00:14:04.072070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T00:11:02.928108Z digest=sha256:338b7c85ec7b524ba0a8c353537acd7a21d1d9a15de010262c4d809f3520b072

Observation 7fa71928-10e1-4b43-a13a-58cf4acff381 · inbound

APT-Agent: Automated Penetration Testing using Large Language Models cites this paper.

APT-Agent: Automated Penetration Testing using Large Language Models Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T00:14:03.930818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T00:11:02.928108Z digest=sha256:d50f5f71d9dbd447db9fa7625d454d5080bd2de987d6475c768351194675a455