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Paper Citation Record · LEDGER

Large Language Models are Built-in Autoregressive Search Engines

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.09612.

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

pith.paper-citation-record.v1
2305.09612 v1

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 2026-08-06T23:52:45.533343Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T23:35:25.586450Z

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 6739c496-9f46-49da-b987-058f959e858a · inbound

SGIC: A Self-Guided Iterative Calibration Framework for RAG cites this paper.

SGIC: A Self-Guided Iterative Calibration Framework for RAG Large Language Models are Built-in Autoregressive Search Engines

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T23:52:45.533343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:52:45.533343Z digest=sha256:92cacb1eb1e21deb0f438f9f9c3d2d96b17ea7e268e12103f89b521086ed78d7

Observation 1f310b8f-bf0c-435e-80b9-af748f1c4898 · inbound

Context-Aware Scientific Knowledge Extraction on Linked Open Data using Large Language Models cites this paper.

Context-Aware Scientific Knowledge Extraction on Linked Open Data using Large Language Models Large Language Models are Built-in Autoregressive Search Engines

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:35:25.654515Z

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=2026-08-06T23:35:19.944869Z digest=sha256:0c778ab5ac22f38f6d62a265dff962bd84aa6f0e50b5e42d3c7403bbce32c396