Paper Citation Record · LEDGER

Residual Matrix Transformers: Scaling the Size of the Residual Stream

As of 9 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 2026-08-09T06:31:02.800959+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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Source-reported events for the cited work

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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; raw_fallback, observed 2026-08-06T22:10:50.278477Z

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.

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

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

Source-reported events for the cited work

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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

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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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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

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

Source-reported events for the cited work

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

Source-reported events for the cited work

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; raw_fallback, observed 2026-08-06T22:10:49.998768Z

Source-reported events for the cited work

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:10:49.724550Z

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.

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

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

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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

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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; raw_fallback, observed 2026-08-06T22:10:49.502237Z

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.

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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Source-reported events for the cited work

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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

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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; raw_fallback, observed 2026-08-06T22:10:49.202895Z

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.

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 2026-08-09T06:31:02.800959+00:00.

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

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

Source-reported events for the cited work

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

Source-reported events for the cited work

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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

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Source-reported events for the cited work

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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; raw_fallback, observed 2026-08-06T22:10:48.551657Z

Source-reported events for the cited work

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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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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

Resolution: 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 2026-08-09T06:31:02.800959+00:00.

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

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

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

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

Reference 27

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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

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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

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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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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

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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

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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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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

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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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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

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

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

Reference 37

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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

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

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

Reference 39

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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

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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

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Source-reported events for the cited work

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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

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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

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Source-reported events for the cited work

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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

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

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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

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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

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Source-reported events for the cited work

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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

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Source-reported events for the cited work

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

Source-reported events for the cited work

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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

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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

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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

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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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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.

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 2026-08-09T06:31:02.800959+00:00.

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.

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 2026-08-09T06:31:02.800959+00:00.

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.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.