Paper Citation Record · LEDGER

Compute Trends Across Three Eras of Machine Learning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2202.05924.

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

pith.paper-citation-record.v1
2202.05924 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:07:15.221368Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T14:24:44.951321Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 6b28299e-48a1-4477-aae8-580342ba57b4 · inbound

Subjective Experience in AI Systems: What Do AI Researchers and the Public Believe? cites this paper.

Subjective Experience in AI Systems: What Do AI Researchers and the Public Believe? Compute Trends Across Three Eras of Machine Learning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T01:07:15.221368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2277bc2-5155-4db4-b335-246700763979 · inbound

Jolting Technologies: Superexponential Acceleration in AI Capabilities and Implications for AGI cites this paper.

Jolting Technologies: Superexponential Acceleration in AI Capabilities and Implications for AGI Compute Trends Across Three Eras of Machine Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T19:10:42.219131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 827f8fde-5e61-4614-9f2b-29fcec617230 · inbound

Polaritonic Machine Learning for Graph-based Data Analysis cites this paper.

Polaritonic Machine Learning for Graph-based Data Analysis Compute Trends Across Three Eras of Machine Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T17:40:15.479498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df7eb637-f546-418f-b698-75356d20a293 · inbound

A Theoretical Framework for Auxiliary-Loss-Free Load Balancing of Sparse Mixture-of-Experts in Large-Scale AI Models cites this paper.

A Theoretical Framework for Auxiliary-Loss-Free Load Balancing of Sparse Mixture-of-Experts in Large-Scale AI Models Compute Trends Across Three Eras of Machine Learning

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-17T02:18:52.584000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3afe5c65-9324-4a5f-9858-716f55c4976f · inbound

LLMOrbit: A Circular Taxonomy of Large Language Models -From Scaling Walls to Agentic AI Systems cites this paper.

LLMOrbit: A Circular Taxonomy of Large Language Models -From Scaling Walls to Agentic AI Systems Compute Trends Across Three Eras of Machine Learning

Reference 136

Resolution: verified exact; arxiv_id, observed 2026-05-16T12:47:53.608714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1521881e-84c9-43e1-a427-10095af4c54c · inbound

Scaling Laws of Global Weather Models cites this paper.

Scaling Laws of Global Weather Models Compute Trends Across Three Eras of Machine Learning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-02T20:36:37.891784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f64c5a3-b694-43df-bffc-e9a8aa97715a · inbound

Position: LLM Inference Should Be Evaluated as Energy-to-Token Production cites this paper.

Position: LLM Inference Should Be Evaluated as Energy-to-Token Production Compute Trends Across Three Eras of Machine Learning

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:27:19.440978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7bbe0931-98e7-46a2-9498-3ec7fb2ad9fa · inbound

MedicalRec: Medical recommender system for image classification without retraining cites this paper.

MedicalRec: Medical recommender system for image classification without retraining Compute Trends Across Three Eras of Machine Learning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:24:44.952660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6c195f4d-60d8-428d-8564-bddcb50a3a89 · inbound

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

Bridging Compute- and Data-Optimal Pretraining Compute Trends Across Three Eras of Machine Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T03:01:54.610918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.