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Paper Citation Record · LEDGER

CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:1911.00359.

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

pith.paper-citation-record.v1
1911.00359 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 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 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:33:55.441839Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T17:02:24.078563Z

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 03788d16-a6c8-4673-98d0-0fb7a9a07835 · inbound

Unsupervised Cross-lingual Representation Learning at Scale cites this paper.

Unsupervised Cross-lingual Representation Learning at Scale CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T16:23:29.600855Z

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.

source=pdf_text observed=2026-05-16T16:23:29.564169Z digest=sha256:69be8b85e6c531c0416326467bd725b3a7dde2b4b4ba639aa486c01f5d9591a2

Observation e3d827c7-880e-4f0b-ba3f-c7f1c1468c77 · inbound

How Much Knowledge Can You Pack Into the Parameters of a Language Model? cites this paper.

How Much Knowledge Can You Pack Into the Parameters of a Language Model? CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:00:28.169302Z

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.

source=arxiv_source observed=2026-05-15T02:00:28.055865Z digest=sha256:d81ad816f5c4c607c8a6beb73072108cd4f0b663046303bd4fb9b1fb97502f3d

Observation 5472dbef-3a53-48ca-a44a-1da109dc35b6 · inbound

The Pile: An 800GB Dataset of Diverse Text for Language Modeling cites this paper.

The Pile: An 800GB Dataset of Diverse Text for Language Modeling CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 120

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T21:35:18.906502Z

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.

source=arxiv_source observed=2026-05-10T21:35:18.513342Z digest=sha256:41795d0f4e64439e06119b9b90e0487d575b2b3c283ecf15439b8deb6f066909

Observation 40b2432e-8c0f-4e45-be7d-32348da2309d · inbound

TinyStories: How Small Can Language Models Be and Still Speak Coherent English? cites this paper.

TinyStories: How Small Can Language Models Be and Still Speak Coherent English? CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-25T07:36:55.190800Z

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.

source=pdf_text observed=2026-05-25T07:36:55.087443Z digest=sha256:1f5c0ab357aa47f7ba951fe0062112cbb1c08b2176a0954e1bf6ccde1f920f57

Observation 5dd9c545-4321-49a5-a26c-66e1f6a9193d · inbound

Scaling Data-Constrained Language Models cites this paper.

Scaling Data-Constrained Language Models CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 129

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:35:21.469750Z

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.

source=pdf_text observed=2026-05-18T01:35:21.150772Z digest=sha256:e066749de01a039bf5d42e6eb4b8f0d37dd2348b049bff1563972dfe8465e518

Observation 0fc3d07e-10cb-4433-b4ff-e7a1743f9cea · inbound

Yi: Open Foundation Models by 01.AI cites this paper.

Yi: Open Foundation Models by 01.AI CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:47:27.920584Z

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.

source=pdf_text observed=2026-05-13T05:47:27.775529Z digest=sha256:3261fda456cff6b5160810bda8686a5304ca4e6dab899f85eebb469df1d1500a

Observation a44804af-48ca-4012-862d-891579879888 · inbound

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training cites this paper.

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 118

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T04:09:36.325229Z

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.

source=pdf_text observed=2026-05-16T04:09:36.019146Z digest=sha256:ba449e02bc0f5bd8990958983738c5a8db064d8f62134111bb3bb6776cf8db6e

Observation c6ceac81-6d16-4aeb-98e0-477ea8bbe813 · inbound

Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model cites this paper.

Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 80

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T08:02:23.384376Z

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.

source=arxiv_source observed=2026-05-19T08:02:23.002090Z digest=sha256:c5263059ef1ecf7c95fa2c2c7eea34bd743781897fa33c8d0569f9557f1cc2fb

Observation 253f9be1-f33b-44e4-8048-6bebdc1a3247 · 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 CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T15:33:55.441839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:33:55.441839Z digest=sha256:21b7e0480184cf2e30acb8d12ab8cda41f05c84a9a374164f9bf6a549dbd129f

Observation a2a851bd-e006-4495-871c-b13c6e4a11ce · inbound

Compute Requirements for Algorithmic Innovation in Frontier AI Models cites this paper.

Compute Requirements for Algorithmic Innovation in Frontier AI Models CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-06T17:52:50.757421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:52:50.757421Z digest=sha256:db215f419c6ecb2d743e11d6f854a2cd59007784eacff73a3752ae9ea1c7e30f

Observation 137788bf-f801-4910-8e92-490cd5ecc825 · inbound

Language Models Improve When Pretraining Data Matches Target Tasks cites this paper.

Language Models Improve When Pretraining Data Matches Target Tasks CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 107

Resolution
unresolved
no resolver link, observed 2026-08-06T16:53:15.031829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:53:15.031829Z digest=sha256:d64a5972358b89f5771c61f927a051207a137a23411be7190970efeb526cd848

Observation 06259a0d-4dd2-4298-a957-7f7bc7057306 · inbound

Video Generators are Robot Policies cites this paper.

Video Generators are Robot Policies CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-15T21:43:37.312838Z

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.

source=pdf_text observed=2026-05-15T21:43:37.162870Z digest=sha256:a58dce9697da79f258d9c81c0ac6b363d63d377416abd5798dba1f2a5c6d92ac

Observation e31f17c5-f02a-4005-8b4d-9c7ae6b0fe08 · inbound

BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining cites this paper.

BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-04T11:16:14.514772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T11:16:14.514772Z digest=sha256:3b71941910617a015530659a4268afe3530d171f5ebb2db3fc4bd44b95c3c11e

Observation c2f873c2-2cd4-4d8d-9414-99f5d0a039c9 · inbound

Low-Resource Safety Failures Are Action Failures, Not Representation Failures cites this paper.

Low-Resource Safety Failures Are Action Failures, Not Representation Failures CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T17:02:24.079935Z

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.

source=arxiv_source observed=2026-06-28T16:59:51.969896Z digest=sha256:d175479ec258ef8a22e2f327adf3ce2c7d36da448c5ee5d9032ec94fc77bbecf

Observation 029975e0-6f6f-401b-aedf-afed6ac63fae · inbound

Token-Native Storage: Read and Write in your Agent's Language cites this paper.

Token-Native Storage: Read and Write in your Agent's Language CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-04T08:28:17.704940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T08:28:17.704940Z digest=sha256:18f4c93f4492ce7891b7d08d9495d889c4cda177ccbfcbe828c71cad9693cc9b

Observation 6a3654bb-915b-476a-a125-591c2aa20ab2 · inbound

Token-Native Storage: Read and Write in your Agent's Language cites this paper.

Token-Native Storage: Read and Write in your Agent's Language CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T01:05:13.475406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:05:13.475406Z digest=sha256:fa29053c8a554205cf02ca5b9bf4f24f34c998f8905f7d63e15d5fb7f1da91c1