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Paper Citation Record · LEDGER

Deep Networks Always Grok and Here is Why

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2402.15555.

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

pith.paper-citation-record.v1
2402.15555 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 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:44:27.049435Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T06:20:59.045952Z

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 c93a662c-a4ad-4b88-b089-80340c6a35b0 · inbound

Grokking vs. Learning: Same Features, Different Encodings cites this paper.

Grokking vs. Learning: Same Features, Different Encodings Deep Networks Always Grok and Here is Why

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-09T14:44:27.049435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:44:27.049435Z digest=sha256:991efa60e3c74151b17562d9a0163e0417a339384cfac1a605a6ae7c247f806a

Observation 516a2bc2-0ad6-4865-97d4-94074518c8a5 · inbound

Mechanistic Insights into Grokking from the Embedding Layer cites this paper.

Mechanistic Insights into Grokking from the Embedding Layer Deep Networks Always Grok and Here is Why

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T15:20:31.770732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:20:31.770732Z digest=sha256:28831aeaea21b61ef8855db00b86a8b692a513bcaaf0df0d6e2c212740fe50fc

Observation 2ba03143-8a1e-4c0b-89e6-ac072f76aff2 · inbound

Learning words in groups: fusion algebras, tensor ranks and grokking cites this paper.

Learning words in groups: fusion algebras, tensor ranks and grokking Deep Networks Always Grok and Here is Why

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-04T22:57:12.131495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:57:12.131495Z digest=sha256:1d9aa1ab839b5b6c736def9bbea893c848a81cc26ec46d3c9605b066949b3224

Observation a53d10fd-8ccc-461a-9e2b-64852680d8fe · inbound

Beyond Binary Out-of-Distribution Detection: Characterizing Distributional Shifts with Multi-Statistic Diffusion Trajectories cites this paper.

Beyond Binary Out-of-Distribution Detection: Characterizing Distributional Shifts with Multi-Statistic Diffusion Trajectories Deep Networks Always Grok and Here is Why

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-18T06:20:59.048212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T06:16:05.522008Z digest=sha256:9928cb5e19f8897de57b7b8dabb0cf388aa1e574ecb78db77bd932209af7bbf5

Observation 32ead466-befe-418d-a11a-4a3cf0e240d4 · inbound

The Geometry of Grokking: Norm Minimization on the Zero-Loss Manifold cites this paper.

The Geometry of Grokking: Norm Minimization on the Zero-Loss Manifold Deep Networks Always Grok and Here is Why

Reference 1970

Resolution
unresolved
no resolver link, observed 2026-08-04T00:32:00.715860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:32:00.715860Z digest=sha256:ca8b3e56499dbb151a734394553c0bd5ab3061abd1883b4a78639c42f2ebec08

Observation 2b3714d6-cf35-4d49-8942-2f6dde13a57d · inbound

HM-Bench: A Comprehensive Benchmark for Multimodal Large Language Models in Hyperspectral Remote Sensing cites this paper.

HM-Bench: A Comprehensive Benchmark for Multimodal Large Language Models in Hyperspectral Remote Sensing Deep Networks Always Grok and Here is Why

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:30:57.708237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T18:06:49.114269Z digest=sha256:c1139b162a1a54db702b9f8953de4efb2dab864ee8bcb7fcac5a615c1228bb9f

Observation 999e456e-aec6-4202-afc3-a61f8c04ed74 · inbound

Complexity of Linear Regions in Self-supervised Deep ReLU Networks cites this paper.

Complexity of Linear Regions in Self-supervised Deep ReLU Networks Deep Networks Always Grok and Here is Why

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:46:48.870088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T04:18:11.839205Z digest=sha256:d42b43b776ca090f991605730cb43eca36b5a2163a22d15dbe1c59b59fdffdad

Observation d16deca6-8068-4b79-8e36-3a106b82ecdd · inbound

Topological Signatures of Grokking cites this paper.

Topological Signatures of Grokking Deep Networks Always Grok and Here is Why

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:01:13.421762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T13:04:54.513192Z digest=sha256:b98e5259106257be8f0e38d6caa81b52d07a9d9ae4c17da921e7e74a899d388a

Observation 999caabc-e53b-4d2c-b143-ea14816eb8fd · inbound

Emergent Generalization by Representation Learning in Artificial Neural Networks cites this paper.

Emergent Generalization by Representation Learning in Artificial Neural Networks Deep Networks Always Grok and Here is Why

Reference 21

Resolution
unresolved
no resolver link, observed 2026-07-14T11:48:27.847402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T11:48:27.847402Z digest=sha256:68d7b875fd8034628e428a7f04ec245c0f8385cfc67b90c2d9d73094087129a2