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Paper Citation Record · LEDGER

CTourLLM: Enhancing LLMs with Chinese Tourism Knowledge

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.12791.

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

pith.paper-citation-record.v1
2407.12791 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:48:42.824482Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T16:18:58.901160Z

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 6f7cdbfc-8aa3-4924-9fae-35cc4117ccce · inbound

A Query-Aware Multi-Path Knowledge Graph Fusion Approach for Enhancing Retrieval-Augmented Generation in Large Language Models cites this paper.

A Query-Aware Multi-Path Knowledge Graph Fusion Approach for Enhancing Retrieval-Augmented Generation in Large Language Models CTourLLM: Enhancing LLMs with Chinese Tourism Knowledge

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T19:48:42.824482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:48:42.824482Z digest=sha256:fa45c5ce4ef8875594f6d7eccbe2cb17c2da896561418e0bbfb37c37cbcb1525

Observation a596fcab-944e-4744-a7c8-81db9032476a · inbound

Large Language Models in the Travel Domain: An Industrial Experience cites this paper.

Large Language Models in the Travel Domain: An Industrial Experience CTourLLM: Enhancing LLMs with Chinese Tourism Knowledge

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:18:59.122512Z

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=pdf_text observed=2026-08-06T16:18:57.796257Z digest=sha256:295c4474fcc8e69e6a0973da7bc9ed9680df7e39d7631ec6462d2bf0b18b2bb4