Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Semantic Segmentation of Legal Documents via Rhetorical Roles
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2112.01836.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T17:55:27.857264Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T17:55:28.278586Z
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 1c34f023-998b-4cc6-bb97-5ed5ed3f7092 · inbound
NyayaAnumana & INLegalLlama: The Largest Indian Legal Judgment Prediction Dataset and Specialized Language Model for Enhanced Decision Analysis cites this paper.
NyayaAnumana & INLegalLlama: The Largest Indian Legal Judgment Prediction Dataset and Specialized Language Model for Enhanced Decision Analysis Semantic Segmentation of Legal Documents via Rhetorical Roles
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T17:55:28.283221Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 527013ec-aaa1-40ac-a94f-3ebb0e9b980a · inbound
AILQA: Evaluating AI-Driven Legal Question Answering Systems for the Indian Legal System cites this paper.
AILQA: Evaluating AI-Driven Legal Question Answering Systems for the Indian Legal System Semantic Segmentation of Legal Documents via Rhetorical Roles
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T14:17:25.913623Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.