Pith. sign in

Paper Citation Record · LEDGER

LLM-Align: Utilizing Large Language Models for Entity Alignment in Knowledge Graphs

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.04690.

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

pith.paper-citation-record.v1
2412.04690 v1

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 2026-08-06T15:51:37.098140Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:51:37.413749Z

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 721466d2-e845-43b0-ae6b-35eee746254b · inbound

Full Triple Matcher: Integrating all triple elements between heterogeneous Knowledge Graphs cites this paper.

Full Triple Matcher: Integrating all triple elements between heterogeneous Knowledge Graphs LLM-Align: Utilizing Large Language Models for Entity Alignment in Knowledge Graphs

Reference 2024

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:51:37.417201Z

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=2026-08-06T15:51:37.098140Z digest=sha256:00625997a220d140fb9cdde922b17237d795a98637fb78edbc6389039d9e8179

Observation 57c9349a-5da9-46f3-98a5-0b21373e5d9f · inbound

Implicit Fine-tuning via Context Engineering: A Curriculum Learning Framework for Multimodal Entity Alignment cites this paper.

Implicit Fine-tuning via Context Engineering: A Curriculum Learning Framework for Multimodal Entity Alignment LLM-Align: Utilizing Large Language Models for Entity Alignment in Knowledge Graphs

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-14T11:01:48.645217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T11:01:48.645217Z digest=sha256:3c21c82f747cfd9a373baa2b6e239e875d120eb11c5178f0b686a8496f8568b5