Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
D4: Improving LLM Pretraining via Document De-Duplication and Diversification
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2308.12284.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:33:55.009360Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T17:38:15.869750Z
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 48bd6354-d573-4255-92f0-aaf829d0d97c · inbound
A Survey of Large Language Models cites this paper.
A Survey of Large Language Models D4: Improving LLM Pretraining via Document De-Duplication and Diversification
Reference 252
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T22:46:40.502583Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 7ba6fee9-d950-4ee2-9fc1-cab5b0dac66c · inbound
Demystifying CLIP Data cites this paper.
Demystifying CLIP Data D4: Improving LLM Pretraining via Document De-Duplication and Diversification
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T09:20:20.244672Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 297283e5-f43c-4334-b970-b5879146e14f · inbound
How Good is Your Wikipedia? Auditing Data Quality for Low-resource and Multilingual NLP cites this paper.
How Good is Your Wikipedia? Auditing Data Quality for Low-resource and Multilingual NLP D4: Improving LLM Pretraining via Document De-Duplication and Diversification
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T17:38:15.872289Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation cc034977-d9fb-489d-9ff7-ad39c71ea6ce · inbound
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain cites this paper.
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain D4: Improving LLM Pretraining via Document De-Duplication and Diversification
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:33:55.009360Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6372e10b-5c5e-4b4b-a850-ae7c47d3a634 · inbound
Towards EnergyGPT: A Large Language Model Specialized for the Energy Sector cites this paper.
Towards EnergyGPT: A Large Language Model Specialized for the Energy Sector D4: Improving LLM Pretraining via Document De-Duplication and Diversification
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T17:42:47.546454Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation ee7dfd12-5d64-48d5-b10c-59e6af1e6360 · inbound
Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation cites this paper.
Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation D4: Improving LLM Pretraining via Document De-Duplication and Diversification
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T08:48:01.008180Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation ae629a64-7b00-43de-a6bf-d23156b206a2 · inbound
Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation cites this paper.
Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation D4: Improving LLM Pretraining via Document De-Duplication and Diversification
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T16:12:12.768405Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 69337ef1-a647-4b0c-8979-f40c380d0ae3 · inbound
Byte-Exact Deduplication in Retrieval-Augmented Generation: A Three-Regime Empirical Analysis Across Public Benchmarks cites this paper.
Byte-Exact Deduplication in Retrieval-Augmented Generation: A Three-Regime Empirical Analysis Across Public Benchmarks D4: Improving LLM Pretraining via Document De-Duplication and Diversification
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T06:26:24.166794Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 3865ca08-8af6-4f3c-afd7-a546f6bfdd0c · inbound
Merlin: Deterministic Byte-Exact Deduplication for Lossless Context Optimization in Large Language Model Inference cites this paper.
Merlin: Deterministic Byte-Exact Deduplication for Lossless Context Optimization in Large Language Model Inference D4: Improving LLM Pretraining via Document De-Duplication and Diversification
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T06:31:29.028876Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.