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Paper Citation Record · LEDGER

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks

As of 8 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2508.08298.

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

pith.paper-citation-record.v1
2508.08298 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:01:42.540642Z

measured 11 of 11 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 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

11 of 11 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 25f70fce-4c82-4e96-a1f8-d2e4b20d22a3 · outbound

This paper cites The Surprising Effectiveness of Test-Time Training for Few-Shot Learning.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks The Surprising Effectiveness of Test-Time Training for Few-Shot Learning

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T00:01:41.698247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:01:41.698247Z digest=sha256:9c6717a978d3e8cd5a77579da9bc6b43a3031f44669a40ac7b2d3addd9155f2c

Observation 0942dab5-ea3c-4272-bbc8-96666fcf4a4d · outbound

This paper cites On the Measure of Intelligence.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks On the Measure of Intelligence

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T00:01:41.795270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:01:41.795270Z digest=sha256:e22bb6da9ce310105744cb1250ba0e2cceb3b59881be73d526423046b655e35b

Observation 405eb33a-611c-444d-98ef-14bfc541b3dc · outbound

This paper cites Looped Transformers for Length Generalization.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks Looped Transformers for Length Generalization

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T00:01:41.852577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:01:41.852577Z digest=sha256:c6ce7cac714cd89a97ca74f61968b1d5e329eb01fbb633f6f346bc70c3b7b582

Observation b570bc0d-839b-42bf-81ee-59a7bd55c658 · outbound

This paper cites Product of Experts with LLMs: Boosting Performance on ARC Is a Matter of Perspective.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks Product of Experts with LLMs: Boosting Performance on ARC Is a Matter of Perspective

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T00:01:41.941186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:01:41.941186Z digest=sha256:85b0f3a2a5b2649a9eb69ae6fb9323ee659dbc1325bb214f389f9900c532cd50

Observation 8e3e0f58-eef0-4c33-95f9-3182c82d87bf · outbound

This paper cites Getting 50\ Redwood Research Substack, June 2024.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks Getting 50\ Redwood Research Substack, June 2024

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:01:43.550164Z

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=2026-08-06T00:01:42.017281Z digest=sha256:6e888d3346a6873af8d8bebf662c519125b1cac0d9f7791fe9b791693212a02e

Observation 108773d4-fbb1-4ee2-889b-4865f2505a0d · outbound

This paper cites Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T00:01:42.106854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:01:42.106854Z digest=sha256:87d671a8e6e530a360e92170998d6624e62127084e7d6252d746e644c246927d

Observation 1af220e7-5a7f-46ff-9b65-0883c3a4db0c · outbound

This paper cites Dunn, Hao Tang, Michelangelo Naim, Dat Nguyen, Wei-Long Zheng, Zenna Tavares, Yewen Pu, and Kevin Ellis.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks Dunn, Hao Tang, Michelangelo Naim, Dat Nguyen, Wei-Long Zheng, Zenna Tavares, Yewen Pu, and Kevin Ellis

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:01:43.333859Z

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=2026-08-06T00:01:42.168912Z digest=sha256:58e14920e5abe0a600f31808d6d6a14e7d5abea7faf0e051b5ae4828434f56b3

Observation b884b270-efbc-447c-9058-5ae03e0ac7b1 · outbound

This paper cites Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T00:01:42.257175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:01:42.257175Z digest=sha256:ccf7fc56dfb3e33ba99d4108b3b17afa6a91ca67916a820d7315383e80fae530

Observation 92e88ad3-4d12-42bf-90d6-5458481acd79 · outbound

This paper cites GLU Variants Improve Transformer.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks GLU Variants Improve Transformer

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T00:01:42.347699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:01:42.347699Z digest=sha256:57b0e42ed6e551364d3b134b5f9a3d14d5d111d920284503f4304c30b5c4167d

Observation 69e52685-3396-42d5-bff3-fd3a2a152942 · outbound

This paper cites ARC-icecuber : Code for 1st place solution to Kaggle's Abstraction and Reasoning Challenge.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks ARC-icecuber : Code for 1st place solution to Kaggle's Abstraction and Reasoning Challenge

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:01:43.140825Z

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=2026-08-06T00:01:42.415760Z digest=sha256:e04274bc12888a963bc1d08e1d790cff447258278ee27d25cf94ad59b7cd34eb

Observation 0cc0ba72-a346-4f0c-86e3-c524cf3772f9 · outbound

This paper cites Example-based Hypernetworks for Out-of-Distribution Generalization.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks Example-based Hypernetworks for Out-of-Distribution Generalization

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T00:01:42.540642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:01:42.540642Z digest=sha256:6c860c40362a5db36ac4208d82c1cf2c4d714845fb6f2f4f6edc188d12f160f4

Pith citing papers

No inbound Pith citation observations are available.