Paper Citation Record · LEDGER

How Do Large Language Models Acquire Factual Knowledge During Pretraining?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2406.11813.

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

pith.paper-citation-record.v1
2406.11813 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T10:26:06.839189Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 68e37456-3641-41d3-9cff-e35646209bff · inbound

Attributing Culture-Conditioned Generations to Pretraining Corpora cites this paper.

Attributing Culture-Conditioned Generations to Pretraining Corpora How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-23T07:07:41.624454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0defba75-5860-4040-ab04-8de92acdfea3 · inbound

Training an LLM-as-a-Judge Model: Pipeline, Insights, and Practical Lessons cites this paper.

Training an LLM-as-a-Judge Model: Pipeline, Insights, and Practical Lessons How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T10:26:06.839189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 786a2993-e95c-46c4-8fb9-e3a7fe1a2b95 · inbound

MaskSearch: A Universal Pre-Training Framework to Enhance Agentic Search Capability cites this paper.

MaskSearch: A Universal Pre-Training Framework to Enhance Agentic Search Capability How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T13:59:15.481097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 576f1372-7fb3-491e-a402-602dd536c745 · inbound

FPEdit: Robust LLM Fingerprinting through Localized Parameter Editing cites this paper.

FPEdit: Robust LLM Fingerprinting through Localized Parameter Editing How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T05:19:08.060448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c6abbd3-45dc-40bd-a36f-f156b46119e3 · inbound

Child-directed speech facilitates production, not comprehension, in BabyLMs cites this paper.

Child-directed speech facilitates production, not comprehension, in BabyLMs How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Reference 158

Resolution: verified exact; arxiv_id, observed 2026-06-28T17:32:24.630221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bae5e28b-d060-40c4-86fb-213fedc71c51 · inbound

Reality Monitoring in Large Language Models: Self-Knowledge That Transforms with Conversation Memory cites this paper.

Reality Monitoring in Large Language Models: Self-Knowledge That Transforms with Conversation Memory How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-31T23:35:42.761763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.