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Paper Citation Record · LEDGER

MegaMath: Pushing the Limits of Open Math Corpora

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2504.02807.

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

pith.paper-citation-record.v1
2504.02807 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:24:48.198898Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T01:09:19.755056Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • 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 ae8240d8-0d89-450b-876c-8366c45afb75 · inbound

DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning cites this paper.

DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning MegaMath: Pushing the Limits of Open Math Corpora

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-16T10:31:04.809020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-16T10:31:04.728005Z digest=sha256:8b19ce9ecb7a52e9e6eccfdb21b572568e756b2a533d79b34ffcb70d42727621

Observation 5bd8c1fb-4044-4c16-ad19-8d19fcb7255b · inbound

Essential-Web v1.0: 24T tokens of organized web data cites this paper.

Essential-Web v1.0: 24T tokens of organized web data MegaMath: Pushing the Limits of Open Math Corpora

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:48.198898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:24:48.198898Z digest=sha256:01f0c8b601f8ab55206e0fcfa7279961ca68286b11406b00ee799c5a9249e790

Observation 5362a314-eefa-40b4-be62-a8ef38279548 · inbound

OctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling cites this paper.

OctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling MegaMath: Pushing the Limits of Open Math Corpora

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:05.518110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:52:05.518110Z digest=sha256:91eafc445c919a7fa43860b99577efb61e8d2f944452eaa61f533f251ba0016c

Observation c3dbeb14-602c-4d70-8146-647992783c2b · inbound

JT-Math: A Multi-Stage Framework for Advanced Mathematical Reasoning in Large Language Models cites this paper.

JT-Math: A Multi-Stage Framework for Advanced Mathematical Reasoning in Large Language Models MegaMath: Pushing the Limits of Open Math Corpora

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T14:11:53.839697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:11:53.839697Z digest=sha256:b5305e67fe464a16ea68e3d2defb43d98a84e46a722d1b3205d71995b2bc6252

Observation c31fc7ee-cb1a-4ff3-9d2d-56d5cfbfcc24 · inbound

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment cites this paper.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment MegaMath: Pushing the Limits of Open Math Corpora

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T13:09:56.610980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:09:56.610980Z digest=sha256:d5ffcadd2fbffbda139fe1d2b439aabcd8051069a3b6df4f1b5c9ebd035613ee

Observation 3fec6ccc-7901-46e4-bde8-044071c19981 · inbound

LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points cites this paper.

LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points MegaMath: Pushing the Limits of Open Math Corpora

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T05:48:28.931061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:48:28.931061Z digest=sha256:5291b258a491f560713f26500c482394abc1bffc5ec6d74a0f619f367d372f95

Observation 0463f911-4d86-4bbf-a55b-5f8430854840 · inbound

Large-Scale Diverse Synthesis for Mid-Training cites this paper.

Large-Scale Diverse Synthesis for Mid-Training MegaMath: Pushing the Limits of Open Math Corpora

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T05:43:18.020122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:43:18.020122Z digest=sha256:72a6969c74d221c703178340d62fed63495c4a707e9dfd643bbcd8c19ace2b3e

Observation eb87b5fe-d310-4f5a-af58-ca3f21acf98a · inbound

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels cites this paper.

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels MegaMath: Pushing the Limits of Open Math Corpora

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-18T08:41:08.385978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-18T08:39:54.747656Z digest=sha256:29e85f958f90386360961245a177998f2e9c8b1dc1dc6bc3e481483ac34881e6

Observation aa55aeea-d813-4721-b0a0-f54de166d265 · inbound

Scaling Latent Reasoning via Looped Language Models cites this paper.

Scaling Latent Reasoning via Looped Language Models MegaMath: Pushing the Limits of Open Math Corpora

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:43:11.900754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T07:43:11.620446Z digest=sha256:4714dcb8811aacb52cd13777d80b7a3d789fdad7e73fadf74be8e80400e69639

Observation c519137d-8acc-439e-8aae-d8059fb67dd6 · inbound

Scaling Latent Reasoning via Looped Language Models cites this paper.

Scaling Latent Reasoning via Looped Language Models MegaMath: Pushing the Limits of Open Math Corpora

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-04T07:31:32.246668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:31:32.246668Z digest=sha256:ea1df8a716f3075b4606084cbc941afb72eec5cef19f62a1f970be363a1710e3

Observation 7eb4dce3-1f12-4166-aedb-7dbdc61ce178 · inbound

Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed cites this paper.

Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed MegaMath: Pushing the Limits of Open Math Corpora

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-16T22:31:19.353758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-16T22:29:08.669964Z digest=sha256:137b3b93bb70466282f51a03cc64fddbbad193436dbe2d539bf0f1a468274188

Observation 920035c9-ef37-49dd-828b-c824dacd4ab9 · inbound

NVIDIA Nemotron 3: Efficient and Open Intelligence cites this paper.

NVIDIA Nemotron 3: Efficient and Open Intelligence MegaMath: Pushing the Limits of Open Math Corpora

Reference 117

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T01:40:42.588491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-18T01:40:42.190369Z digest=sha256:1544b59110b8868388870204ee8e36c0aaa2e8c70083feeec12ffdb1a8df95cc

Observation 5cf21938-6d7c-40af-9c31-44290f068b6c · inbound

Attention Editing: A Versatile Framework for Cross-Architecture Attention Conversion cites this paper.

Attention Editing: A Versatile Framework for Cross-Architecture Attention Conversion MegaMath: Pushing the Limits of Open Math Corpora

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:30:51.690662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T19:47:34.869184Z digest=sha256:62a8ba4bca501240254b36f126a247548ef52fdad2714ce1eccd83ae7253af3b

Observation 863957c5-600b-4ccb-8719-4faa51e1a0be · inbound

TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications? cites this paper.

TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications? MegaMath: Pushing the Limits of Open Math Corpora

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:28:14.631847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T11:23:34.256279Z digest=sha256:d98e5f718c3b44a048ea716a628a49440dc826a46723818e8d3eefb44d3c0f92

Observation 2b0c20e5-000b-4970-a554-4417eb13a451 · inbound

Which Models Are Our Models Built On? Auditing Invisible Dependencies in Modern LLMs cites this paper.

Which Models Are Our Models Built On? Auditing Invisible Dependencies in Modern LLMs MegaMath: Pushing the Limits of Open Math Corpora

Reference 81

Resolution
verified exact
arxiv_id, observed 2026-07-03T10:37:56.560275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-27T09:57:14.328157Z digest=sha256:a1283cefe1d6cc9919364e2a696538f1bb7ce0c01431c65acf7cd91c8394a88c

Observation 49691499-9901-4955-a08f-fa2d8ef49915 · inbound

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale cites this paper.

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale MegaMath: Pushing the Limits of Open Math Corpora

Reference 159

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T22:17:25.660218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-07-02T22:10:59.568675Z digest=sha256:d3418d9215ac6f7257791f6e3c03e57a7467a21516f209f1d6e2e1eb6261f86a

Observation c8cf01ed-0b31-4c08-af7a-0b74010af2dc · inbound

Sumi: Open Uniform Diffusion Language Model from Scratch cites this paper.

Sumi: Open Uniform Diffusion Language Model from Scratch MegaMath: Pushing the Limits of Open Math Corpora

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-04T01:09:19.756409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-06-26T20:34:43.697141Z digest=sha256:c3bca9fe2fd8aa6471114a6e65007c5e25740461b1a43c4dc195c769ab6d173e

Observation 1d01093d-1049-4caf-8613-982f95d96780 · inbound

DataOrchestra: Learning to Orchestrate Per-Example Curation of Pretraining Data cites this paper.

DataOrchestra: Learning to Orchestrate Per-Example Curation of Pretraining Data MegaMath: Pushing the Limits of Open Math Corpora

Reference 28

Resolution
unresolved
no resolver link, observed 2026-07-31T07:01:45.800728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T07:01:45.800728Z digest=sha256:8be12429f88ccf66688322161388e72fb835e15288f079c00463d5c79b9890b3