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Paper Citation Record · LEDGER

Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2408.07705.

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

pith.paper-citation-record.v1
2408.07705 v1

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 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:35:20.802453Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T01:07:19.875775Z

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 6400443a-5a82-40ca-a72f-ebc664c96f20 · inbound

LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion cites this paper.

LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Models

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-23T01:07:19.880880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T01:05:38.969311Z digest=sha256:cde4e42a82c854b9233020363020cc32df93ec9b46ee9bd5eb9219de04f60de5

Observation 0adbc7bf-c92b-46fd-8aef-5ec6460394cf · inbound

From Unstructured Communication to Intelligent RAG: Multi-Agent Automation for Supply Chain Knowledge Bases cites this paper.

From Unstructured Communication to Intelligent RAG: Multi-Agent Automation for Supply Chain Knowledge Bases Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Models

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T23:35:20.802453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:35:20.802453Z digest=sha256:1a614a83546d3c95fa946c03118b408a6740764a3153240bab97b485820ab7e5

Observation e93617a1-f691-4c20-860e-e540ef269c6d · inbound

Structural Consequences of Policy-Based Interventions on the Global Supply Chain Network cites this paper.

Structural Consequences of Policy-Based Interventions on the Global Supply Chain Network Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Models

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:41:01.403021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T15:53:55.645486Z digest=sha256:6fc1d753341725c0506d43a22d9722b515e975bfc2df9e0b4b247cc5c53df35a

Observation 80ac8d3c-1dce-4c09-9600-8c1035a01469 · inbound

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training cites this paper.

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Models

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:46:04.094071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-10T03:04:54.146481Z digest=sha256:e4777bf95c221f4d7bd5b97229edd36a1f803d95320cfb9df3d29059e80c4b1c

Observation b05f74e0-712c-431f-8344-2f817096f19a · inbound

Reconstructing temporal multi-relational firm networks at scale using large language models. The case of the semiconductor industry cites this paper.

Reconstructing temporal multi-relational firm networks at scale using large language models. The case of the semiconductor industry Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Models

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-19T19:37:43.750153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T19:36:30.855340Z digest=sha256:08fa5640b53548502d31663b862c1a581213c04a3b4103fa057a6ed58c764dfd