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Paper Citation Record · LEDGER

The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2010.15581.

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

pith.paper-citation-record.v1
2010.15581 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:42:14.209745Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T21:06:14.589654Z

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 3ee0395f-7e45-4a79-8e5a-7d84fb2048fa · inbound

Towards Industrial Convergence : Understanding the evolution of scientific norms and practices in the field of AI cites this paper.

Towards Industrial Convergence : Understanding the evolution of scientific norms and practices in the field of AI The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T14:42:14.209745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:42:14.209745Z digest=sha256:470dad04311fe43e3f56cb483d3ce69eb17fe22c30459cd470d72a16b1020cd1

Observation 2d5f5922-d932-4e21-a156-78716f55c847 · inbound

Translate With Care: Addressing Gender Bias, Neutrality, and Reasoning in Large Language Model Translations cites this paper.

Translate With Care: Addressing Gender Bias, Neutrality, and Reasoning in Large Language Model Translations The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T12:04:10.694908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:04:10.694908Z digest=sha256:6ef753954900236716bb7bca2b10f08142498632cfc84350ec068871bbd44623

Observation 550d7fa0-dd41-4635-bb6a-ee9e03eba04f · inbound

What Makes Local Updates Effective: The Role of Data Heterogeneity and Smoothness cites this paper.

What Makes Local Updates Effective: The Role of Data Heterogeneity and Smoothness The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T21:27:17.852556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:27:17.852556Z digest=sha256:ecac5b621cb92efe0d5c978b2f1f96ac8eeb21a62b5c7ec0083d0615606e5455

Observation 08d8265a-2896-40d3-9821-7c47e43ea8c6 · inbound

Irresponsible AI: big tech's influence on AI research and associated impacts cites this paper.

Irresponsible AI: big tech's influence on AI research and associated impacts The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-03T19:43:34.082162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T19:43:34.082162Z digest=sha256:c2717bc86693dd4f74db8b46303ce165db08425a18d8e9bab670bed61e63e553

Observation 9ca42598-4362-4f4d-ad70-afa76a365cc8 · inbound

How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI cites this paper.

How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-16T13:20:57.637879Z

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=2026-05-16T13:20:39.676562Z digest=sha256:a05864fb107ba174b9c956209f7493b95cc8ef41ca4c0ead5c7bf20ab4573528

Observation 951e31e0-e591-42b0-bc7f-c291f8d73092 · inbound

How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI cites this paper.

How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-03T09:36:13.261972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T09:36:13.261972Z digest=sha256:f1470c6783315cbc6490f27f085713e6d7d6cd5e3f538f59276c82c4bc1e62d3

Observation 65ee1b2b-b85a-4c92-ad3d-b3c4906c0363 · inbound

The Quantization Trap: Breaking Linear Scaling Laws in Multi-Hop Reasoning cites this paper.

The Quantization Trap: Breaking Linear Scaling Laws in Multi-Hop Reasoning The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-15T22:30:22.041952Z

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=2026-05-15T22:27:49.943714Z digest=sha256:4092011e43082a8b3280a9d076c9c306d330aa26ae8b3ca4bdd876c559d0d231

Observation 95fe61ce-a3e0-46bb-9969-a762baf7f7c2 · inbound

Cost-of-Ethics Crisis: Beliefs, Decisions, and Justifications in the Job Searches of Computer Science Students in Canada and the United States cites this paper.

Cost-of-Ethics Crisis: Beliefs, Decisions, and Justifications in the Job Searches of Computer Science Students in Canada and the United States The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 200

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:36:27.217372Z

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=2026-05-12T04:07:52.323371Z digest=sha256:46f9f582cf65b30ddbc2b821664f65a9e8686ac90fc9445d7fa2b377f63d4aed

Observation aea7f12e-259d-403a-94b8-896135e5e875 · inbound

Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis cites this paper.

Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 109

Resolution
verified exact
arxiv_id, observed 2026-05-20T20:28:59.964195Z

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=2026-05-20T20:24:16.373261Z digest=sha256:296186befaf47aeb7460f23c41be9a640aee57b12dc474963320002be15f0e32

Observation 75edc250-e803-458c-a715-0ac9a41f7184 · inbound

HRM-Text: Efficient Pretraining Beyond Scaling cites this paper.

HRM-Text: Efficient Pretraining Beyond Scaling The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:43:59.019904Z

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=2026-05-21T05:41:41.397554Z digest=sha256:913b2ee31fe2f9f29978d1bdac5f5212897b49420c4f88936ec3be72c5c8c863

Observation b6626b1e-3209-48fd-a1c3-14c2e8b8a235 · inbound

Barriers to Evidence in AI-Related Cases and the Privatization of Proof cites this paper.

Barriers to Evidence in AI-Related Cases and the Privatization of Proof The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-22T07:31:13.852163Z

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=2026-05-22T07:30:55.511139Z digest=sha256:bc4ba4ead17faacfe9184dae3ba7dfe6cadbed24b2c56a08bc9915011847e3d0

Observation 3384b524-d3f2-4370-b5fe-f45bff5eee37 · inbound

Evaluation of ML Resource Utilization Requires Model Life Cycle Assessment cites this paper.

Evaluation of ML Resource Utilization Requires Model Life Cycle Assessment The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T21:06:14.591434Z

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=2026-06-28T17:27:19.467192Z digest=sha256:a9d66820569e2f6feea229be71f068958f18857a7ad97a6a4cbe7aa46245e5b6