Paper Citation Record · LEDGER

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation

As of 16 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2507.11645.

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

pith.paper-citation-record.v1
2507.11645 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:10:12.049200Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

verified exact2
verified fuzzy3
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c1b0c093-a3fd-4da3-8bd6-f5b7980d12dd · outbound

This paper cites Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:11.983022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 321bca95-2504-49fe-8057-58dbfc96130c · outbound

This paper cites Omnigrok: Grokking Beyond Algorithmic Data.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Omnigrok: Grokking Beyond Algorithmic Data

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:11.987412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9833673b-e870-4fb0-a300-ce4dd4d1257b · outbound

This paper cites Controlling Grokking with Nonlinearity and Data Symmetry.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Controlling Grokking with Nonlinearity and Data Symmetry

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:10:12.177954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4640b4bf-014c-46ee-9539-8bb677542cd6 · outbound

This paper cites Towards Understanding Grokking: An Effective Theory of Representation Learning.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Towards Understanding Grokking: An Effective Theory of Representation Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:11.999826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebe579d2-aed2-4c0e-9407-812e84bd3d39 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:12.004091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf93456b-62ec-4741-8947-329e7efc6015 · outbound

This paper cites Learning the symmetric group: large from small.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Learning the symmetric group: large from small

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:10:12.142461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f9faaf10-b663-4e5e-8343-e0cdadab1ac0 · outbound

This paper cites Deep Grokking: Would Deep Neural Networks Generalize Better?.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Deep Grokking: Would Deep Neural Networks Generalize Better?

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:12.014069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01c2c97e-85bf-44d8-8523-e217c39227f5 · outbound

This paper cites Hidden progress in deep learning: Sgd learns parities near the computational limit.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Hidden progress in deep learning: Sgd learns parities near the computational limit

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:10:12.241148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 395d889a-a00e-4510-94d5-26b4df7a6887 · outbound

This paper cites Progress measures for grokking via mechanistic interpretability.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Progress measures for grokking via mechanistic interpretability

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:12.021781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cd45044-4c53-4b66-bda9-e970f91f6fd2 · outbound

This paper cites Grokking modular arithmetic.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Grokking modular arithmetic

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:12.025593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98562052-9fce-4287-8bdd-85b62afc78b0 · outbound

This paper cites Explaining grokking through circuit efficiency.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Explaining grokking through circuit efficiency

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:12.030195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0de9c568-2877-4528-847a-0708c3dc5375 · outbound

This paper cites Progress Measures for Grokking on Real-world Tasks.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Progress Measures for Grokking on Real-world Tasks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:12.033626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 639f2b71-ed70-49b3-8694-57858d1aaa97 · outbound

This paper cites A Tale of Two Circuits: Grokking as Competition of Sparse and Dense Subnetworks.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation A Tale of Two Circuits: Grokking as Competition of Sparse and Dense Subnetworks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:12.037121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5160df7-789c-4008-9a5e-ee1fe6eb7365 · outbound

This paper cites To grok or not to grok: Disentangling generalization and memorization on corrupted algorithmic datasets.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation To grok or not to grok: Disentangling generalization and memorization on corrupted algorithmic datasets

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T17:10:12.041000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66f24b82-4f00-4f4f-bd03-24842f9c923a · outbound

This paper cites Dropout as a Bayesian approximation: Representing model uncertainty in deep learning.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Dropout as a Bayesian approximation: Representing model uncertainty in deep learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:10:12.229876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4b0da438-eed5-40f6-a7dc-689d99ec2ae5 · outbound

This paper cites Tikeng Notsawo, Hattie Zhou, Mohammad Pezeshki, Irina Rish, and Guillaume Dumas.

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation Tikeng Notsawo, Hattie Zhou, Mohammad Pezeshki, Irina Rish, and Guillaume Dumas

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:10:12.217988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.