Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.01375.
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 2026-08-07T13:33:52.994596Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T20:43:25.282010Z
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 3e28a103-38f6-4bb9-8364-33140453541d · inbound
A Practice of Post-Training on Llama-3 70B with Optimal Selection of Additional Language Mixture Ratio cites this paper.
A Practice of Post-Training on Llama-3 70B with Optimal Selection of Additional Language Mixture Ratio D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T20:43:25.284698Z
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 16c2a519-496c-4d04-b4fa-96a085159c1a · inbound
Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives cites this paper.
Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:33:52.994596Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 99f93e6a-c6c4-410d-9d37-7a1d6681e838 · inbound
SLAI T-Rex: Full-Parameter Post-training of the DeepSeek-V4 Family on Ascend SuperPOD cites this paper.
SLAI T-Rex: Full-Parameter Post-training of the DeepSeek-V4 Family on Ascend SuperPOD D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T10:42:37.077298Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.