Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.17050.
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 2026-08-15T20:26:09.748495Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T14:26:56.980904Z
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 70674e28-8d26-439d-a67c-57e555bc3d65 · inbound
Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey cites this paper.
Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models
Reference 116
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T19:15:25.416255Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b02e7f3-4305-40a8-8072-870703617e73 · inbound
Evaluating the Performance of RAG Methods for Conversational AI in the Airport Domain cites this paper.
Evaluating the Performance of RAG Methods for Conversational AI in the Airport Domain Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:26:09.748495Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0bb6bbc3-b4bb-4c1c-aadd-29dfd4a7304b · inbound
Vision Meets Language: A RAG-Augmented YOLOv8 Framework for Coffee Disease Diagnosis and Farmer Assistance cites this paper.
Vision Meets Language: A RAG-Augmented YOLOv8 Framework for Coffee Disease Diagnosis and Farmer Assistance Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models
Reference 13
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T14:26:57.039952Z
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.