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Paper Citation Record · LEDGER

Methods for Computing Legal Document Similarity: A Comparative Study

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2004.12307.

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

pith.paper-citation-record.v1
2004.12307 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:21:44.179487Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T13:04:04.878069Z

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 9156f688-2870-4cdc-af74-ac7f0c768923 · inbound

Rethinking Word Similarity: Semantic Similarity through Classification Confusion cites this paper.

Rethinking Word Similarity: Semantic Similarity through Classification Confusion Methods for Computing Legal Document Similarity: A Comparative Study

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-08T18:21:44.179487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T18:21:44.179487Z digest=sha256:2df21d8f7944c8140cde1123f200956e353b11141f6fd38ca910608aebffc271

Observation a4e39c9b-e191-4008-bb2d-24c44069ce06 · inbound

Hybrid Topic-Semantic Labeling and Graph Embeddings for Unsupervised Legal Document Clustering cites this paper.

Hybrid Topic-Semantic Labeling and Graph Embeddings for Unsupervised Legal Document Clustering Methods for Computing Legal Document Similarity: A Comparative Study

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:04:04.957410Z

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=2026-08-05T13:04:03.944312Z digest=sha256:a0c0cfda4d99b1212f252b8b648d5881dc0c93e41f6ae8ebd282e68dcd939657