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Paper Citation Record · LEDGER

Document-level Relation Extraction as Semantic Segmentation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2106.03618.

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

pith.paper-citation-record.v1
2106.03618 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:49:32.321639Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T14:49:32.603988Z

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 bc3ec281-fb41-42dd-85a6-061ed74bab0b · inbound

Multi-Relation Extraction in Entity Pairs using Global Context cites this paper.

Multi-Relation Extraction in Entity Pairs using Global Context Document-level Relation Extraction as Semantic Segmentation

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.610995Z

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=2026-08-06T14:49:32.321639Z digest=sha256:57171b95403f3206bc16b224a98bc7cd365240e1604218996bc6fdc1501454ea

Observation 5d54ea59-eef2-4b79-b3fc-d49a1d389d47 · inbound

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models cites this paper.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Document-level Relation Extraction as Semantic Segmentation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-07-31T18:32:12.311471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T18:32:12.311471Z digest=sha256:08f6596b08840e1d13dcf2cac74065f301691ebdbfb1b67f32c072c9a5697088