Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.09046.
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 2026-08-15T17:21:00.821676Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T18:10:16.452962Z
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 bf3fb357-6b67-46bf-a792-c4472e18d132 · inbound
InputSnatch: Stealing Input in LLM Services via Timing Side-Channel Attacks cites this paper.
InputSnatch: Stealing Input in LLM Services via Timing Side-Channel Attacks HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T11:29:29.416916Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ec287d2b-6674-4c17-9b83-5809a7a31d2a · inbound
Orchestration for Domain-specific Edge-Cloud Language Models cites this paper.
Orchestration for Domain-specific Edge-Cloud Language Models HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T18:10:16.524929Z
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 948fa22d-4946-4b85-b474-d2059ae553bf · inbound
All for law and law for all: Adaptive RAG Pipeline for Legal Research cites this paper.
All for law and law for all: Adaptive RAG Pipeline for Legal Research HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T17:21:00.821676Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.