Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Scaling Laws for Fact Memorization of Large Language Models
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.15720.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T20:25:25.312186Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T11:03:13.742445Z
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 a138a281-cd56-4c8c-9641-a145c6b01daa · inbound
Paying Attention to Facts: Quantifying the Knowledge Capacity of Attention Layers cites this paper.
Paying Attention to Facts: Quantifying the Knowledge Capacity of Attention Layers Scaling Laws for Fact Memorization of Large Language Models
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T20:25:25.312186Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7faffe95-ed68-470d-baec-db6421a8562d · inbound
How much do language models memorize? cites this paper.
How much do language models memorize? Scaling Laws for Fact Memorization of Large Language Models
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:35:39.123074Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3b0430dd-2d52-4545-bbce-a5629b15bb01 · inbound
ABench-Physics: Benchmarking Physical Reasoning in LLMs via High-Difficulty and Dynamic Physics Problems cites this paper.
ABench-Physics: Benchmarking Physical Reasoning in LLMs via High-Difficulty and Dynamic Physics Problems Scaling Laws for Fact Memorization of Large Language Models
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:46:46.924233Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fab2e529-8271-4bb6-a0c2-cd32c520b693 · inbound
Learning Facts at Scale with Active Reading cites this paper.
Learning Facts at Scale with Active Reading Scaling Laws for Fact Memorization of Large Language Models
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T21:05:45.224515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3bd2fa5e-86b0-4234-b545-371b74f5aa04 · inbound
Predictable Confabulations: Factual Recall by LLMs Scales with Model Size and Topic Frequency cites this paper.
Predictable Confabulations: Factual Recall by LLMs Scales with Model Size and Topic Frequency Scaling Laws for Fact Memorization of Large Language Models
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T11:03:13.743817Z
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.