Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Enhancing Legal Document Retrieval: A Multi-Phase Approach with Large Language Models
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2403.18093.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T18:07:57.354694Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T15:58:10.533168Z
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 a308d9d4-c877-4b59-a415-cd912daa7f17 · inbound
PaSa: An LLM Agent for Comprehensive Academic Paper Search cites this paper.
PaSa: An LLM Agent for Comprehensive Academic Paper Search Enhancing Legal Document Retrieval: A Multi-Phase Approach with Large Language Models
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T19:28:32.632433Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1c4cd241-4338-40ad-b7b0-9a37b176f1de · inbound
Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining cites this paper.
Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining Enhancing Legal Document Retrieval: A Multi-Phase Approach with Large Language Models
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:58:10.539496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 4cd00b6d-ea1f-49ff-9ac5-dd21f53d88e8 · inbound
Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection cites this paper.
Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection Enhancing Legal Document Retrieval: A Multi-Phase Approach with Large Language Models
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T18:07:57.354694Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.