Paper Citation Record · LEDGER

Learning Curve Theory

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2102.04074.

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

pith.paper-citation-record.v1
2102.04074 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 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 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:44:23.751019Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:20:00.916264Z

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 45c58d3f-80c3-4e80-a78c-d0f601f51ca5 · inbound

Recursive Inference Scaling: A Winning Path to Scalable Inference in Language and Multimodal Systems cites this paper.

Recursive Inference Scaling: A Winning Path to Scalable Inference in Language and Multimodal Systems Learning Curve Theory

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T12:44:23.751019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86728ef3-148a-4115-bd3c-0a7e2e41ad9b · inbound

Scaling Pre-training to One Hundred Billion Data for Vision Language Models cites this paper.

Scaling Pre-training to One Hundred Billion Data for Vision Language Models Learning Curve Theory

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-08T12:12:30.714593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9335bd3f-f79a-4924-a653-ccd17f123656 · inbound

Superposition Yields Robust Neural Scaling cites this paper.

Superposition Yields Robust Neural Scaling Learning Curve Theory

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:36:25.559183Z

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.

Observation 7fbdc2cd-c03f-4aed-8ad7-76703561d66d · inbound

Training Dynamics Underlying Language Model Scaling Laws: Loss Deceleration and Zero-Sum Learning cites this paper.

Training Dynamics Underlying Language Model Scaling Laws: Loss Deceleration and Zero-Sum Learning Learning Curve Theory

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:20.400174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cac885d1-a04b-405d-ae7c-90021ba568a7 · inbound

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens cites this paper.

Beyond Scaling Curves: Internal Dynamics of Neural Networks Through the NTK Lens Learning Curve Theory

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T19:40:36.494987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07a45857-41e7-4472-b49e-101600fd9895 · inbound

Universal One-third Time Scaling in Learning Peaked Distributions cites this paper.

Universal One-third Time Scaling in Learning Peaked Distributions Learning Curve Theory

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-03T05:01:12.187219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d418aea-4b31-4d20-b748-bbd2a6815ef9 · inbound

Inverse Depth Scaling From Most Layers Being Similar cites this paper.

Inverse Depth Scaling From Most Layers Being Similar Learning Curve Theory

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T04:07:45.786899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 235d3e58-be75-4b97-b5d2-4306416d93bf · inbound

Sharp feature-learning transitions and Bayes-optimal neural scaling laws in extensive-width networks cites this paper.

Sharp feature-learning transitions and Bayes-optimal neural scaling laws in extensive-width networks Learning Curve Theory

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:56:18.750204Z

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.

Observation a3ab7b4c-3a6f-4f72-9e56-bc8d1fdef615 · inbound

From One-Pass SGD to Data Reuse: Mini-Batch Scaling Laws in Sketched Linear Regression cites this paper.

From One-Pass SGD to Data Reuse: Mini-Batch Scaling Laws in Sketched Linear Regression Learning Curve Theory

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:14:45.615817Z

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.

Observation 4b09068c-8428-4656-9670-596aecf42846 · inbound

Augment Engineering: A Methodology for Multi-Tool AI Orchestration Across Professional Domains cites this paper.

Augment Engineering: A Methodology for Multi-Tool AI Orchestration Across Professional Domains Learning Curve Theory

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:34:45.618841Z

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.

Observation f22ae927-b23a-4854-a72a-23c05b9b162f · inbound

Law of Neural Interaction: Depth-Width Shape, Interaction Efficiency, and Generalization cites this paper.

Law of Neural Interaction: Depth-Width Shape, Interaction Efficiency, and Generalization Learning Curve Theory

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-06-29T14:23:31.002966Z

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.

Observation a0e73cf4-1cba-4cf7-93eb-13aca9f53cb3 · inbound

Structure and Scale in Simplicial Sequence Modelling cites this paper.

Structure and Scale in Simplicial Sequence Modelling Learning Curve Theory

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:16:14.974663Z

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.

Observation 46a8f6cf-b85d-4c48-b8e3-4a965914f7b3 · inbound

Critical Percolation as a Synthetic Data Model for Interpretability cites this paper.

Critical Percolation as a Synthetic Data Model for Interpretability Learning Curve Theory

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:49:29.628962Z

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.

Observation aeb5af57-86f2-432d-b3c5-80e2a93cba6b · inbound

Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients cites this paper.

Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients Learning Curve Theory

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:20:00.917928Z

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.

Observation ba03f533-3a3a-408c-8684-59c3d6ad8e73 · inbound

Sketched Linear Contrastive Learning: Approximation, Optimization, and Statistical Scaling cites this paper.

Sketched Linear Contrastive Learning: Approximation, Optimization, and Statistical Scaling Learning Curve Theory

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T12:59:52.795739Z

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.

Observation 014a5a7b-1927-423b-bd7b-7fac0db2ffe2 · inbound

Smooth Scaling Laws Hide Stepwise Token Learning cites this paper.

Smooth Scaling Laws Hide Stepwise Token Learning Learning Curve Theory

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-30T08:14:26.530134Z

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.

Observation 3f4bf71f-0bff-4138-90f4-0f80368459b3 · inbound

Smooth Scaling Laws Hide Stepwise Token Learning cites this paper.

Smooth Scaling Laws Hide Stepwise Token Learning Learning Curve Theory

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-13T07:15:03.029543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d7164c8-5714-45ea-b080-b0d2cab4c437 · inbound

Data-Efficient Deep Learning: Empirical Guidelines for Training Set Size Estimation in Inertial Sensor Classification cites this paper.

Data-Efficient Deep Learning: Empirical Guidelines for Training Set Size Estimation in Inertial Sensor Classification Learning Curve Theory

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-13T03:17:51.964379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2c5a61a-614a-4487-b41e-2c254051024d · inbound

Position: Stop Reactively Patching Your Model Every Time and Start Proactive Test-Driven AI Development cites this paper.

Position: Stop Reactively Patching Your Model Every Time and Start Proactive Test-Driven AI Development Learning Curve Theory

Reference 126

Resolution: unresolved; no resolver link, observed 2026-08-02T07:40:25.534753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.