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Paper Citation Record · LEDGER

Residual Matrix Transformers: Scaling the Size of the Residual Stream

As of 14 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 4 inbound Pith citation observations for arXiv:2506.22696.

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

pith.paper-citation-record.v1
2506.22696 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:10:42.664065Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T06:57:48.485750Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:56:27.336351Z

Reference resolution

57 of 57 outbound references displayed

  • verified exact4
  • verified fuzzy20
  • unresolved32
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 32c371ae-288a-4e5c-ad8d-9b95749285c7 · outbound

This paper cites GPT-4 Technical Report.

Residual Matrix Transformers: Scaling the Size of the Residual Stream GPT-4 Technical Report

Reference 1

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no resolver link, observed 2026-08-06T22:10:37.761768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:37.761768Z digest=sha256:e7f55185a4c4429548d4bbf3f7995a66975eaa54f8b84da4a442c1d1b0d68dbb

Observation 1c3987d3-2016-4994-a19c-cd558fb9021a · outbound

This paper cites Data on notable ai models, 2024.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Data on notable ai models, 2024

Reference 2

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:37.850440Z digest=sha256:764c2487ab0029f7abc2a1540d56828c97f570aa482936a0176f7ebe20748ee5

Observation 6bb4684d-8903-43b2-91e1-777e6c740b40 · outbound

This paper cites an unresolved cited work.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Unresolved cited work

Reference 3

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no resolver link, observed 2026-08-06T22:10:37.940979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:37.940979Z digest=sha256:04c1d67f508fa2b049e3eaa5a36a47ac369f109f912007eea6560affab1438e0

Observation 143a60d4-5f6e-4944-bb99-00be61621381 · outbound

This paper cites ReZero is All You Need: Fast Convergence at Large Depth.

Residual Matrix Transformers: Scaling the Size of the Residual Stream ReZero is All You Need: Fast Convergence at Large Depth

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:38.027642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:38.027642Z digest=sha256:b49b7e1a9308851d1a3f01f1df96cabc244831bc15471c26861a30c908df960f

Observation 7df33577-9d16-41ac-8b03-ac2e16bf7043 · outbound

This paper cites L., Gao, J., and Choi, Y.

Residual Matrix Transformers: Scaling the Size of the Residual Stream L., Gao, J., and Choi, Y

Reference 5

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no resolver link, observed 2026-08-06T22:10:38.114071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:38.114071Z digest=sha256:64d6f120d93968b56bc18972bba15f6c8e10874142a704951912ac8e858dc131

Observation 0a4cbcbc-b951-4730-920d-13c76e6794b7 · outbound

This paper cites J., Leary, C., Maclaurin, D., Necula, G., Paszke, A., Vander P las, J., Wanderman- M ilne, S., and Zhang, Q.

Residual Matrix Transformers: Scaling the Size of the Residual Stream J., Leary, C., Maclaurin, D., Necula, G., Paszke, A., Vander P las, J., Wanderman- M ilne, S., and Zhang, Q

Reference 6

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no resolver link, observed 2026-08-06T22:10:38.227792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:38.227792Z digest=sha256:c2c51892df9017a377e3d254ccc83ab2c81b7e6a9bd236327dbf56d5fe4d6391

Observation c9cea776-30bd-4710-8ab8-05ec64e84447 · outbound

This paper cites Highway transformer: Self-gating enhanced self-attentive networks.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Highway transformer: Self-gating enhanced self-attentive networks

Reference 7

Resolution
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no resolver link, observed 2026-08-06T22:10:38.287379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:38.287379Z digest=sha256:ebc6cc9beea0b22cd2ff30f5049fa1d2051d06874adb20fd3b55bd56b6118180

Observation 77782c8b-fae9-4901-9ab8-aabd10cf125c · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 8

Resolution
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no resolver link, observed 2026-08-06T22:10:38.357759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:38.357759Z digest=sha256:e89058d03b0c08687a4d3bcb22da49f52d0f4ae8cd557973478ac4452156949b

Observation e3911a57-0c6e-4013-a2d6-a585c28fc786 · outbound

This paper cites and Gu, A.

Residual Matrix Transformers: Scaling the Size of the Residual Stream and Gu, A

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:38.459876Z digest=sha256:5fc03df30cbe7e209f7257728856bbb0515d0102aac076909fa69d9a2367173a

Observation 2ff2c62a-7d03-453f-b20c-14181287d758 · outbound

This paper cites The practitioner’s guide to the maximal update parameterization.

Residual Matrix Transformers: Scaling the Size of the Residual Stream The practitioner’s guide to the maximal update parameterization

Reference 10

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:38.580547Z digest=sha256:e97eb5b8d2fab196b716784a50f2a4c44ff60925f3f260f6e69943778c74531c

Observation 7c1b5811-dfc4-4588-baf8-55b8a18f7683 · outbound

This paper cites Exploiting deep representations for neural machine translation.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Exploiting deep representations for neural machine translation

Reference 11

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no resolver link, observed 2026-08-06T22:10:38.689710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:38.689710Z digest=sha256:781209a6754965f4c98e242d0812741ce25e6a65f89dd23acc3b9e9a1f0dc778

Observation 6471b11d-8e29-416e-8878-81298e5d8b56 · outbound

This paper cites Dynamic layer aggregation for neural machine translation with routing-by-agreement.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Dynamic layer aggregation for neural machine translation with routing-by-agreement

Reference 12

Resolution
verified exact
doi, observed 2026-08-06T22:10:43.496475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:38.773045Z digest=sha256:8db27e4dc135ddfe767c94b9fab61f64c495bbc4e85c07e57068c5270d60ef1e

Observation 3926092e-feac-42eb-9cf6-16529d3789e7 · outbound

This paper cites M., Tong, S., Lepikhin, D., Xu, Y., Krikun, M., Zhou, Y., Yu, A.

Residual Matrix Transformers: Scaling the Size of the Residual Stream M., Tong, S., Lepikhin, D., Xu, Y., Krikun, M., Zhou, Y., Yu, A

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:38.836683Z digest=sha256:68d6227c652c55a758e348e5383bb0009668755f10f0821080f42292f462d7ef

Observation 27a6a7e3-8a21-4b6a-9751-9d758db5459e · outbound

This paper cites The Llama 3 Herd of Models.

Residual Matrix Transformers: Scaling the Size of the Residual Stream The Llama 3 Herd of Models

Reference 14

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unresolved
no resolver link, observed 2026-08-06T22:10:38.895675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:38.895675Z digest=sha256:11e50d35e346823a95bf19bd0bcd71663bb6d9e405bc82000ce6597b955e963e

Observation d68e213b-d7fa-43e5-b2a6-65f2dac4298e · outbound

This paper cites A mathematical framework for transformer circuits.

Residual Matrix Transformers: Scaling the Size of the Residual Stream A mathematical framework for transformer circuits

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:38.957499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:38.957499Z digest=sha256:8cc18cbb131fa24fb11130aa7079cfa3e7855dea4ee1b78863235ac2dbb32c7b

Observation e5596dc8-c3e0-428b-bd1e-3342fd278c75 · outbound

This paper cites Depth-wise attention ( DWA tt): A layer fusion method for data-efficient classification.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Depth-wise attention ( DWA tt): A layer fusion method for data-efficient classification

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:39.025580Z digest=sha256:08c8f05cb2591237d5e265c4a9c2fe85e5ba225a687830a25ca26d9d72063921

Observation 94b9bbe9-0595-4df8-9d49-bfa3a90304a2 · outbound

This paper cites Switch transformers: scaling to trillion parameter models with simple and efficient sparsity.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Switch transformers: scaling to trillion parameter models with simple and efficient sparsity

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:48.848672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:39.127169Z digest=sha256:be687eeebc2ebcea6813ed9607e457d90f667c337ad347a04f12baa43d0e5b86

Observation 71def2d5-51fb-4d4b-bb34-fe3b9aba7768 · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

Residual Matrix Transformers: Scaling the Size of the Residual Stream The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 18

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no resolver link, observed 2026-08-06T22:10:39.216652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:39.216652Z digest=sha256:0b7ae79a3c698b3626fa2c223f6b16729b58cb8109cb757fc82cd6dfdd139733

Observation fcab7e4d-22fa-4a93-93d6-25f5a1db61ea · outbound

This paper cites A framework for few-shot language model evaluation, 12 2023.

Residual Matrix Transformers: Scaling the Size of the Residual Stream A framework for few-shot language model evaluation, 12 2023

Reference 19

Resolution
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no resolver link, observed 2026-08-06T22:10:39.301860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:39.301860Z digest=sha256:243199761d0989af5e65df0834f43ac469c8f6aceb1f24c22c30bca9d8211458

Observation 549250fd-ad90-4797-8b5a-d4e02e08b644 · outbound

This paper cites Transformer feed-forward layers are key-value memories.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Transformer feed-forward layers are key-value memories

Reference 20

Resolution
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no resolver link, observed 2026-08-06T22:10:39.393140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:39.393140Z digest=sha256:4aa17139cb9d06ddd24a2a924f94b221f138b785897cd8501b013bebe0890601

Observation 306abe5c-86d6-409b-8547-1d8c22e868d0 · outbound

This paper cites and Bengio, Y.

Residual Matrix Transformers: Scaling the Size of the Residual Stream and Bengio, Y

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:39.490319Z digest=sha256:673e648b5a2f3b36906b3ad0f76c0bd4c375ea8fccaac097bd52ac3c4a2cb583

Observation ccca6fd6-9854-471c-b0dc-2bbd76751228 · outbound

This paper cites F., Keller, P.

Residual Matrix Transformers: Scaling the Size of the Residual Stream F., Keller, P

Reference 22

Resolution
verified exact
doi, observed 2026-08-06T22:10:43.237138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:39.577236Z digest=sha256:3bc66e98bcfc012dbf10e771dfa0616be48591a8ca0dea67c88e6ebf6d7e17fc

Observation 55c1cd0a-64fa-4c66-8d45-3bbddaf7ba91 · outbound

This paper cites Improving language modeling using densely connected recurrent neural networks.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Improving language modeling using densely connected recurrent neural networks

Reference 23

Resolution
verified exact
doi, observed 2026-08-06T22:10:43.029950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:39.742103Z digest=sha256:ae08b43cc49f93de1f1b75e10ff13c04ac6282c70c47ff3cbdf0e199616d79ac

Observation 3e4f1d3a-2e16-44d8-a194-31845d29ba0a · outbound

This paper cites Openwebtext corpus.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Openwebtext corpus

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:48.274655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:39.812409Z digest=sha256:ade89be506314a04a66f600c6a4026d15a1000af3ce7fe49b41219d472f148e2

Observation a449fe91-9057-4cf1-a18b-7e3eaa3216fe · outbound

This paper cites Levanter , 2024.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Levanter , 2024

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-06T22:10:48.100444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:39.881434Z digest=sha256:2af508358d0b0b1e0e9515d1a03bbe0940eda779826b8d47bd76f5b5b3fa438c

Observation 11ec86af-93fa-4281-ac2b-45a438c216ba · outbound

This paper cites A., Welbl, J., Clark, A., Hennigan, T., Noland, E., Millican, K., van den Driessche, G., Damoc, B., Guy, A., Osindero, S., Simonyan, K., Elsen, E., Vinyals, O., Rae, J.

Residual Matrix Transformers: Scaling the Size of the Residual Stream A., Welbl, J., Clark, A., Hennigan, T., Noland, E., Millican, K., van den Driessche, G., Damoc, B., Guy, A., Osindero, S., Simonyan, K., Elsen, E., Vinyals, O., Rae, J

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-06T22:10:47.931783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:39.957622Z digest=sha256:28a80a4fd0280bed667186ab8e16f7b057e6d6eacac3d28724715fb4921da57b

Observation 65d1f1cc-3ef4-4974-bf72-c3eb93caac67 · outbound

This paper cites an unresolved cited work.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Unresolved cited work

Reference 27

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unresolved
no resolver link, observed 2026-08-06T22:10:40.044197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:40.044197Z digest=sha256:10f7bf6bf12ef28f644972536cdaa38770b5a21119b6e93021953c4b19c3d4e6

Observation 6e4c6bac-9ba4-41d9-b0e0-2679f0943100 · outbound

This paper cites S., Perez, F., Ba, J., and Volkovs, M.

Residual Matrix Transformers: Scaling the Size of the Residual Stream S., Perez, F., Ba, J., and Volkovs, M

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:47.607651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:40.131319Z digest=sha256:da0f7636d9b8f8fcd4ee9ad445a2fc1926704a63319a26c0fc8f64b1ab0c5ac7

Observation 908dce63-c9ac-4143-92cc-91d066e1e0d2 · outbound

This paper cites Mixtral of Experts.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Mixtral of Experts

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:40.230675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:40.230675Z digest=sha256:7771af0d7a4af1619566acc82fafe28fc788a54e10e22213e81cf4a752885633

Observation 355aed13-bfd0-4d7a-86b9-c8dd8c98ee09 · outbound

This paper cites Scaling Laws for Neural Language Models.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Scaling Laws for Neural Language Models

Reference 30

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unresolved
no resolver link, observed 2026-08-06T22:10:40.323401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:40.323401Z digest=sha256:038eff9684692b11c188fd7a35303df15bcd54e2ed8e31b256550fed424b9f50

Observation 5a40469d-96e9-4e9d-8fae-7054e109e9ae · outbound

This paper cites A., Khyalia, S., Jung, J., Goka, H., and Lee, H.

Residual Matrix Transformers: Scaling the Size of the Residual Stream A., Khyalia, S., Jung, J., Goka, H., and Lee, H

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:47.308625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:40.438103Z digest=sha256:397c9ee074bc39f988af917936b5b5f78fcbf1594a47e79a2eded6a34c636c93

Observation 08a0971b-4f05-4e5f-b123-580de6ae7277 · outbound

This paper cites and Garcia, C.

Residual Matrix Transformers: Scaling the Size of the Residual Stream and Garcia, C

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:47.015386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:40.575474Z digest=sha256:2e47096e15ec390ea887c13fedc06bb3a40cfbc6cf97c22b14be625f85de4107

Observation 64c3ee2c-3eab-4881-95c2-59631ab744e8 · outbound

This paper cites Correlation matrix memories.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Correlation matrix memories

Reference 33

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unresolved
no resolver link, observed 2026-08-06T22:10:40.676503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:40.676503Z digest=sha256:a023c5277e7337cf5ed6d569d4c00ed5638a8a1533f86717d60d699680d62a66

Observation b4f17652-0086-4c9d-946b-e78d9355e1e4 · outbound

This paper cites S., Viguier, S., and Ligozat, A.-L.

Residual Matrix Transformers: Scaling the Size of the Residual Stream S., Viguier, S., and Ligozat, A.-L

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:46.737432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:40.808780Z digest=sha256:5853d020cc46a56bcd742de89d9e66a5da38aaadb07ff531038012676dc8c75f

Observation c16a5847-53ea-4045-a571-22bf147949e8 · outbound

This paper cites Locating and editing factual associations in gpt.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Locating and editing factual associations in gpt

Reference 35

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unresolved
no resolver link, observed 2026-08-06T22:10:40.884403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:40.884403Z digest=sha256:f64a0776efa367bb05f3b1f1f4d5b5786d71b372d081fa85a09b9444dda5646c

Observation 4236ebcd-f3f7-4ed5-8e92-ae0dbae54c1c · outbound

This paper cites Pointer sentinel mixture models, 2016.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Pointer sentinel mixture models, 2016

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:40.972787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:40.972787Z digest=sha256:3c12f28865c5d72700f8c3c8e15017590ace8313df2011680a0d385e4dcdb1e7

Observation 206e45f8-9c1e-483a-801e-a90bfdc243f7 · outbound

This paper cites an unresolved cited work.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:10:46.460833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:41.072184Z digest=sha256:327f72b9504acdaa9421fa2c7a1bff7da747efc23325e74917df6e3681a1f33e

Observation b1175a3e-4148-47ab-ae2e-c6fc4e52c955 · outbound

This paper cites N., Bernardi, R., Pezzelle, S., Baroni, M., Boleda, G., and Fernández, R.

Residual Matrix Transformers: Scaling the Size of the Residual Stream N., Bernardi, R., Pezzelle, S., Baroni, M., Boleda, G., and Fernández, R

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:46.142709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:41.191219Z digest=sha256:45a4c82f608bb8d7485efea066f95b3e4b16d13f8ea783418cc9fc18311415df

Observation 18085f3e-d60b-4c3d-8093-32895328e37c · outbound

This paper cites an unresolved cited work.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Unresolved cited work

Reference 39

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no resolver link, observed 2026-08-06T22:10:41.311087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:41.311087Z digest=sha256:02f1976fcbeb9eb725b9972c522532632edcc1671061edc8d15f89ba98e53904

Observation fb38678a-f1c6-417b-b348-f1fde8ca02f8 · outbound

This paper cites Language models are unsupervised multitask learners.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Language models are unsupervised multitask learners

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:41.383599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:41.383599Z digest=sha256:a26b4bd1d99a51d53ad2037b8cb86616c6d5a92418f7d86b14b73acd05f8e906

Observation d7431f82-9ad5-499c-b812-860dc7ddcfb8 · outbound

This paper cites WinoGrande: An Adversarial Winograd Schema Challenge at Scale.

Residual Matrix Transformers: Scaling the Size of the Residual Stream WinoGrande: An Adversarial Winograd Schema Challenge at Scale

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:41.445154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:41.445154Z digest=sha256:1dee4d5b28ed4dc4781310a47ef8acbb70f952dd5e2d05ff44125922844fd130

Observation e0d92e61-5ff9-4f73-9d7e-3101552fcf9f · outbound

This paper cites Dense information flow for neural machine translation.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Dense information flow for neural machine translation

Reference 42

Resolution
verified exact
doi, observed 2026-08-06T22:10:42.842398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:41.539224Z digest=sha256:cebaffecdce611de538142196d807fb36f4f93246192f5cb296979480bbfbd18

Observation 95eb7219-1915-42ee-8692-65a282ad4ccc · outbound

This paper cites NormFormer: Improved Transformer Pretraining with Extra Normalization.

Residual Matrix Transformers: Scaling the Size of the Residual Stream NormFormer: Improved Transformer Pretraining with Extra Normalization

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:41.617138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:41.617138Z digest=sha256:2ca9d49931404852c70a92aeeb630862a40a1c451d49510a388d09f719ef1a18

Observation 9cf1d0b2-bd1e-4a6a-a027-751c00864274 · outbound

This paper cites Highway Networks.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Highway Networks

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:41.707792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:41.707792Z digest=sha256:dbe516140de47306893e497849fe99a7be65ac8156f14f5efa05bf59a8ca3cc5

Observation 475dd86c-63e0-4f7a-8407-f7db7c93e97d · outbound

This paper cites Energy and policy considerations for deep learning in NLP.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Energy and policy considerations for deep learning in NLP

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:41.781657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:41.781657Z digest=sha256:5c621143d39065d66a818972bc0c0ee042f6c2351bc73bb14d6b040e23d5b051

Observation 2a7940ea-10ff-4130-9db4-3614e1d6c4f1 · outbound

This paper cites Retentive Network: A Successor to Transformer for Large Language Models.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Retentive Network: A Successor to Transformer for Large Language Models

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:41.843365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:41.843365Z digest=sha256:8b5187a14cfed53d5d76f930b22c0bdd20e048050ac3f9b36e6f22ecd9f3bf7f

Observation a66badff-3400-4cc6-bc6c-92c056048304 · outbound

This paper cites N., Kaiser, L., and Polosukhin, I.

Residual Matrix Transformers: Scaling the Size of the Residual Stream N., Kaiser, L., and Polosukhin, I

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:41.928686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:41.928686Z digest=sha256:1565f2743c92d709acc1a2baf0683a2496e402d7b4036ecd4e4e63707ddc20bd

Observation ea500b1a-5515-4f4a-935e-322268ff2939 · outbound

This paper cites Will we run out of data? Limits of LLM scaling based on human-generated data.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Will we run out of data? Limits of LLM scaling based on human-generated data

Reference 48

Resolution
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no resolver link, observed 2026-08-06T22:10:42.018922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:42.018922Z digest=sha256:c661c9858c0360a1369edc9e7818179da909c8acee063d8429d81f9ae85c528b

Observation c46b6888-8933-431f-a842-4e0fff70b41b · outbound

This paper cites DeepNet: Scaling Transformers to 1,000 Layers.

Residual Matrix Transformers: Scaling the Size of the Residual Stream DeepNet: Scaling Transformers to 1,000 Layers

Reference 49

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T22:10:43.941942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:42.086374Z digest=sha256:b16f2895b2ccb00b9af32e45abcd21c5301bb3188273feb19debb530a59724fc

Observation 7617ae6f-8976-4a2b-b583-67a199e1a4dc · outbound

This paper cites Sustainable ai: Environmental implications, challenges and opportunities.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Sustainable ai: Environmental implications, challenges and opportunities

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:45.855046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:42.151420Z digest=sha256:7a1185f738bd2bd800393fa0f53a449518c9b06b3073930baff2962b15bfed4d

Observation 5802b0e6-5736-4f42-8ea7-df2c1b7868ee · outbound

This paper cites On layer normalization in the transformer architecture.

Residual Matrix Transformers: Scaling the Size of the Residual Stream On layer normalization in the transformer architecture

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:42.219073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:42.219073Z digest=sha256:8483fd40bf471bd66b5bb46124be753dab1cd6681bf55c0eb5a6aaddf443a0e8

Observation 796d5560-502e-49fa-ba23-81aaa5ae8566 · outbound

This paper cites Rewiring the transformer with depth-wise LSTM s.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Rewiring the transformer with depth-wise LSTM s

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:45.580802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:42.278612Z digest=sha256:1c3ba6b937745548f84e43a83ecf342f31002eb57a97a8ea49c3391f256a9b41

Observation e8464d62-9500-459d-8730-31e1add1f216 · outbound

This paper cites Understanding and improving layer normalization.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Understanding and improving layer normalization

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:45.315939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:42.388022Z digest=sha256:0608acf50b5984ddda18859207b293fb51d5d8183002862b0efc7bc5ba7c7141

Observation 9ef79cd2-3e8c-42f8-bd63-e806e3e52afd · outbound

This paper cites J., Babuschkin, I., Sidor, S., Liu, X., Farhi, D., Ryder, N., Pachocki, J., Chen, W., and Gao, J.

Residual Matrix Transformers: Scaling the Size of the Residual Stream J., Babuschkin, I., Sidor, S., Liu, X., Farhi, D., Ryder, N., Pachocki, J., Chen, W., and Gao, J

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:45.028453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:42.458155Z digest=sha256:e345c80a3e7c99c857af45a0caac6e184f1907529d14bf6b14a90e5c90657c15

Observation cc2393ac-79da-45c2-8088-c4dac56f5837 · outbound

This paper cites Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:42.530396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:42.530396Z digest=sha256:7f375bc0978e5ba232aa7b1a994f3d23d842b7a3e30564e4816657a519098ace

Observation e1723c6c-4bbe-4f1d-b712-1721fbba7c28 · outbound

This paper cites Ready-to-go transmission projects 2023.

Residual Matrix Transformers: Scaling the Size of the Residual Stream Ready-to-go transmission projects 2023

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:10:44.742616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-06T22:10:42.600570Z digest=sha256:f7893aab6555ad7d08738c2866c41570e4a1e08d3bdc3a07511ab728f47beaa8

Observation f7e03f87-cc49-4c6c-8e81-cfd3780c8aed · outbound

This paper cites write newline.

Residual Matrix Transformers: Scaling the Size of the Residual Stream write newline

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T22:10:42.664065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:10:42.664065Z digest=sha256:729eb7aaaca4a32bb81605e4f4a341ba478006f43fba493ddaf7ad5063840229

Pith citing papers

Observation c3bb16f6-fb4f-437d-a3b1-720f21918be0 · inbound

mHC: Manifold-Constrained Hyper-Connections cites this paper.

mHC: Manifold-Constrained Hyper-Connections Residual Matrix Transformers: Scaling the Size of the Residual Stream

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-15T12:31:48.048670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-15T12:31:48.001520Z digest=sha256:d1e2611e3c9970e6174522d81e03c64b7eb5a0108e6655efee4728d48d2a42ea

Observation 1a5b3ce4-2940-49e8-a909-3a073882034f · inbound

KromHC: Manifold-Constrained Hyper-Connections with Kronecker-Product Residual Matrices cites this paper.

KromHC: Manifold-Constrained Hyper-Connections with Kronecker-Product Residual Matrices Residual Matrix Transformers: Scaling the Size of the Residual Stream

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-03T06:57:48.485750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:57:48.485750Z digest=sha256:1d77431268236c5d70f298bf73629279d17cf4b5015d549b0d164719dee3d216

Observation 05bcf0ab-3cf0-47aa-b7c8-e760f495da94 · inbound

Attention Residuals cites this paper.

Attention Residuals Residual Matrix Transformers: Scaling the Size of the Residual Stream

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-21T06:39:04.510323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-21T06:39:04.312270Z digest=sha256:4b5718f09ef586ea6fca7f1ed05c5e416c9ef8a1ed780ed93dad7938e29825fa

Observation c0e0e803-3f12-4048-ac6e-0b18a95d4216 · inbound

Analyzing Stream Collapse in Hyper-Connections: From Diagnosis to Mitigation cites this paper.

Analyzing Stream Collapse in Hyper-Connections: From Diagnosis to Mitigation Residual Matrix Transformers: Scaling the Size of the Residual Stream

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-02T01:56:27.339163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-28T11:27:13.506226Z digest=sha256:00faa91d07ecb094e6f5a04004bd190969ee022eddde1de0300fd4ee1c448892