Paper Citation Record · LEDGER

Eight Things to Know about Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2304.00612.

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

pith.paper-citation-record.v1
2304.00612 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:28:54.566550Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T22:30:44.673645Z

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 22901f12-6aee-453d-a420-2136140930e5 · inbound

Large Language Models are not Fair Evaluators cites this paper.

Large Language Models are not Fair Evaluators Eight Things to Know about Large Language Models

Reference 58

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T12:10:42.382325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dcb24634-105e-4a14-aba2-a73be0d84226 · inbound

Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment cites this paper.

Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment Eight Things to Know about Large Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:30:44.676823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2f604192-d41f-4cc2-b78c-7afdfb280203 · inbound

On the Fitness Landscape in the $NK$ Model cites this paper.

On the Fitness Landscape in the $NK$ Model Eight Things to Know about Large Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T19:28:54.566550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 256750f4-c4fb-4fd2-a179-c3811af52299 · inbound

Evaluating Artificial Intelligence Through a Christian Understanding of Human Flourishing cites this paper.

Evaluating Artificial Intelligence Through a Christian Understanding of Human Flourishing Eight Things to Know about Large Language Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:03:12.583813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 638218e7-c835-45e6-bf9c-833989584ca8 · inbound

TurboVec: A Case Study in Cost-Efficient Private Retrieval for Enterprise RAG via Codebook-Oblivious Quantization cites this paper.

TurboVec: A Case Study in Cost-Efficient Private Retrieval for Enterprise RAG via Codebook-Oblivious Quantization Eight Things to Know about Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T19:26:39.137474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.