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Paper Citation Record · LEDGER

Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 28 inbound Pith citation observations for arXiv:2401.16380.

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

pith.paper-citation-record.v1
2401.16380 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:34:25.396774Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T18:40:03.338957Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
  • unresolved0
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  • 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 02309a5f-c760-4444-960b-69d1a27fb55e · inbound

DataComp-LM: In search of the next generation of training sets for language models cites this paper.

DataComp-LM: In search of the next generation of training sets for language models Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 121

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:58:17.106296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-17T22:58:16.523267Z digest=sha256:90906792e813bebbf20e5c3e925e47143ddb7cfb9085fa2a25c0ab4440475580

Observation 37c7d081-73c9-4f4d-8dc9-55aaf38085f6 · inbound

Scaling Synthetic Data Creation with 1,000,000,000 Personas cites this paper.

Scaling Synthetic Data Creation with 1,000,000,000 Personas Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-16T00:03:55.762502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-16T00:03:55.599967Z digest=sha256:1a268c4df7d74143822b1941f5fac8d6061e751de49420d407c6e84c82614149

Observation 17d4afc8-d201-4acc-86ef-31fa3d0e2908 · inbound

Training Bilingual LMs with Data Constraints in the Targeted Language cites this paper.

Training Bilingual LMs with Data Constraints in the Targeted Language Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 36

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no resolver link, observed 2026-08-12T17:04:34.414352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T17:04:34.414352Z digest=sha256:4091d48df6121b8a5144c6bd387289e107b77733feef1ea207b8889eb7d14f66

Observation 0bb99622-29b9-4701-874d-1973b87d96e4 · inbound

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models cites this paper.

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 127

Resolution
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no resolver link, observed 2026-08-11T22:57:01.844727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:57:01.844727Z digest=sha256:b2bbac021550d4bd68db0c7da63fc9499043e471b05454f64d90768e109b2b1a

Observation 9ffb7686-a2bd-458c-bdb3-12e24d32dfa9 · inbound

Alignment at Pre-training! Towards Native Alignment for Arabic LLMs cites this paper.

Alignment at Pre-training! Towards Native Alignment for Arabic LLMs Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T22:41:17.466195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:41:17.466195Z digest=sha256:63173bf13798798dd6e32fbf922e68abc182ef315402e866731ec0ec0b9bcc1c

Observation 0072b76d-d4a5-4c68-a15f-c7261545e3b4 · inbound

Arabic Stable LM: Adapting Stable LM 2 1.6B to Arabic cites this paper.

Arabic Stable LM: Adapting Stable LM 2 1.6B to Arabic Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-11T21:37:27.014464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T21:37:27.014464Z digest=sha256:c677ec3d5d8d4ab03b126d49ced2b6a79d153bb632519b3abda11f35e4d81d40

Observation a7fe0c9c-f9ef-4640-ad48-61535f4d34a8 · inbound

C3oT: Generating Shorter Chain-of-Thought without Compromising Effectiveness cites this paper.

C3oT: Generating Shorter Chain-of-Thought without Compromising Effectiveness Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T14:47:03.937151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:47:03.937151Z digest=sha256:0e9948feefb5ba1db5a166c29a526dd8445e1bb6cb0a0b9208e79a4280507c8f

Observation 8594e581-c03c-4434-a486-e744ee97243e · inbound

Reformulation for Pretraining Data Augmentation cites this paper.

Reformulation for Pretraining Data Augmentation Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 18

Resolution
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no resolver link, observed 2026-08-08T23:08:36.139142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T23:08:36.139142Z digest=sha256:ca594af1c25a1743bfb8d7e6423330964d89a5300b22f3fc4716655a7ff30649

Observation 3615383a-f02e-4296-8e7f-55743a133445 · inbound

Synthesize-on-Graph: Knowledgeable Synthetic Data Generation for Continue Pre-training of Large Language Models cites this paper.

Synthesize-on-Graph: Knowledgeable Synthetic Data Generation for Continue Pre-training of Large Language Models Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-16T04:34:25.396774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:34:25.396774Z digest=sha256:beb876b88172d0c663c6319af2ef5d4a6a0d822191b96d8a438d2cb1821b522b

Observation 9f419473-e6d6-437e-a476-a105c49ab2c8 · inbound

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training cites this paper.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 87

Resolution
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no resolver link, observed 2026-08-07T15:36:06.407101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:36:06.407101Z digest=sha256:d5358ac1943cefd77385c0cec124b998d457893b7846dcb208f1e55f1d8ee658

Observation 4f4b3451-b7e6-4fd0-b7a2-5c1fb5ce070b · inbound

A Survey of LLM $\times$ DATA cites this paper.

A Survey of LLM $\times$ DATA Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 282

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:13.493874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:13.493874Z digest=sha256:86c58570de78f584993a95e478f9d8c9fb6ca178d99eb23c4afb19ebf5108e8a

Observation af7264e8-e402-4814-abb7-82e5a8c83fc3 · inbound

GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthetic Data Generation cites this paper.

GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthetic Data Generation Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T14:00:31.493097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:00:31.493097Z digest=sha256:7c15bc41317232359e1c4b42f81a6201fe3d1f70f7dc54de30b67e7b0153a2d7

Observation 02e4352e-6e95-453e-bf01-72a906a47bcc · inbound

MCTS-Refined CoT: High-Quality Fine-Tuning Data for LLM-Based Repository Issue Resolution cites this paper.

MCTS-Refined CoT: High-Quality Fine-Tuning Data for LLM-Based Repository Issue Resolution Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T00:49:35.734975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:49:35.734975Z digest=sha256:6e21b0ecb6b7cf6393b9da50d318500591e0d6522a188dbe52bce5d01d478140

Observation 91dfd06b-e4fa-466a-a3dd-78dcc7940c74 · inbound

Assessing the Role of Data Quality in Training Bilingual Language Models cites this paper.

Assessing the Role of Data Quality in Training Bilingual Language Models Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:57.762055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:42:57.762055Z digest=sha256:8530f5c7294de484f5be3b21597db1456626c7cb1565a169788f94e38baa4871

Observation 99425188-6df5-4939-8e9a-84c61e481abd · inbound

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

Language Models Improve When Pretraining Data Matches Target Tasks Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T16:53:11.574563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:53:11.574563Z digest=sha256:f26885ae7992eb3e08503522145d43bff1cec36d927603f95c6b0c43876a0e25

Observation 7e21040e-dc80-4fcf-b486-7984e959cd8e · inbound

Kimi K2: Open Agentic Intelligence cites this paper.

Kimi K2: Open Agentic Intelligence Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-10T17:49:28.021895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T17:49:27.926646Z digest=sha256:9e1476ee7b8aae528b43a9d1736553f3d17f13dfb658ec00289d3f231fa7c05d

Observation 6119b7e9-03cc-420c-8198-ee7929aee534 · inbound

Using Scaling Laws for Data Source Utility Estimation in Domain-Specific Pre-Training cites this paper.

Using Scaling Laws for Data Source Utility Estimation in Domain-Specific Pre-Training Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 22

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unresolved
no resolver link, observed 2026-08-06T11:59:52.215099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:59:52.215099Z digest=sha256:8b21b747513d6a20e64547bea105ec0b8c436a31563b4f2eb3bd6bcc516fbc40

Observation b7cb313f-fe78-4e76-a415-c4a08e6d6355 · inbound

Generative Data Refinement: Just Ask for Better Data cites this paper.

Generative Data Refinement: Just Ask for Better Data Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-04T20:24:40.684171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T20:24:40.684171Z digest=sha256:0f7bfd9b7770f1900bb5d1a94cd5f4779beea53ce6219212a747bc3369736194

Observation 9728fc77-56a6-4b02-a71b-7b87c4917d69 · 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 Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-04T11:16:12.298065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T11:16:12.298065Z digest=sha256:54c737712d241a39f331283d3a76d59fd215a2f08cae173525753f8d975f69a4

Observation a580307e-5ade-4b1e-982e-2dde6978f624 · inbound

ZAYA1-8B Technical Report cites this paper.

ZAYA1-8B Technical Report Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 47

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T17:26:05.118696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-08T17:36:37.182196Z digest=sha256:85380a4664b5382ecc7a063b962728464cc6fe9554adb41eb44b46923d9a5a36

Observation f621cbe0-1ef0-47c0-88e1-703d42b76fd5 · inbound

Vibe Calibration: Autonomous Bring-up of a 112-Qubit Superconducting Quantum Processor by a Skill-Orchestrating Language Agent cites this paper.

Vibe Calibration: Autonomous Bring-up of a 112-Qubit Superconducting Quantum Processor by a Skill-Orchestrating Language Agent Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:59:42.729670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-26T10:43:19.166363Z digest=sha256:b70937087865f26381b1b3a3bb1ea5b817bb7b20f3600fd3a7075c32943fcb00

Observation 42bca175-271d-48b7-a0e5-f53d2198f0f5 · inbound

ZONOS2 Technical Report cites this paper.

ZONOS2 Technical Report Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 73

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T18:40:03.340356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-25T22:37:15.072758Z digest=sha256:69cd4d01a7adf6cacad6d2ff1b71b98e31e626b9ee51e98b79c245f99e7a3752

Observation fef361ec-cad6-44c8-a7c2-94facd75bc68 · inbound

ZONOS2 Technical Report cites this paper.

ZONOS2 Technical Report Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 73

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T18:15:58.939099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-29T02:07:31.791835Z digest=sha256:1ef2387dcf782a0842bd1b442b5d26424c182a3a269bde9299b077b1510e4c1c

Observation 4087f884-0132-4e81-a79f-f6e9992d15b0 · inbound

Internal Data Repetition Destroys Language Models cites this paper.

Internal Data Repetition Destroys Language Models Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:49:57.887355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-26T00:12:56.745617Z digest=sha256:3318f4af04b66e9f1081f838de87602672028665b63f3f0c8b9a780e5cf417f0

Observation 8df12efa-006b-48c5-959b-d55de576737f · inbound

Data Quality over Capacity: Internalizing Documents into LoRA Adapters for Closed-Book QA cites this paper.

Data Quality over Capacity: Internalizing Documents into LoRA Adapters for Closed-Book QA Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 8

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no resolver link, observed 2026-08-01T06:29:15.333711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T06:29:15.333711Z digest=sha256:4345aa6ef76bc3c265e5fd62b08b9922bf76b1752c6a0cb505419b8775e62583

Observation 1fe88210-30ff-441f-a150-5440c9ca3cc8 · inbound

Bridging Compute- and Data-Optimal Pretraining cites this paper.

Bridging Compute- and Data-Optimal Pretraining Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-01T03:02:02.501376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:02:02.501376Z digest=sha256:9e11eb3a3393b26a978dcdcc36d812b74a50b6d423bbf18ca2ce1f15d33c98c7

Observation e44e48f2-f40a-4c30-be2b-8fd78c83eff5 · inbound

ZUNA1.1: A more flexible EEG foundation model for Denoising and Super-resolution cites this paper.

ZUNA1.1: A more flexible EEG foundation model for Denoising and Super-resolution Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 57

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unresolved
no resolver link, observed 2026-08-01T09:51:53.287233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T09:51:53.287233Z digest=sha256:9202694a39cbf0bb2d8a80675ee8af48b86386fcad384b9c3b577cf6890048aa

Observation 444cfb4f-cdf9-472d-976a-a057fb97ee46 · inbound

The Announcement Carries the Cue: Markup, Boundaries, and the Notation of Pre-Training Corpora cites this paper.

The Announcement Carries the Cue: Markup, Boundaries, and the Notation of Pre-Training Corpora Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 55

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unresolved
no resolver link, observed 2026-08-11T23:46:08.722972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:46:08.722972Z digest=sha256:638206d43712e2d986fb12c2c9d36959ad00ec87372cc168882fad65b619159b