Paper Citation Record · LEDGER

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions

As of 8 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2509.07236.

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

pith.paper-citation-record.v1
2509.07236 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T22:41:54.761613Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

42 of 42 outbound references displayed

verified exact4
verified fuzzy17
unresolved20
parse uncertain0
malformed identifier0
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External citation measurements

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Outbound references

Observation f318ae6d-1d8c-492e-88fa-902104ca142b · outbound

This paper cites Widrow, M.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Widrow, M

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.353408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a6fff925-9891-4183-8f6e-163a71825d58 · outbound

This paper cites Cauchy, M´ethode g´en´erale pour la r´esolution des syst`emes d’´equations simultan´ees, Comptes Rendus 25 (1847) 536–538.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Cauchy, M´ethode g´en´erale pour la r´esolution des syst`emes d’´equations simultan´ees, Comptes Rendus 25 (1847) 536–538

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.340029Z

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Observation 7917ce59-963a-455d-941b-b92855fc47e5 · outbound

This paper cites Robbins, S.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Robbins, S

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.326653Z

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Observation 60678532-0a81-4282-9599-47c990f0ab80 · outbound

This paper cites Widrow, M.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Widrow, M

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.314012Z

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Observation d9acfe9c-5c5a-4697-8bab-ad9171a0cea6 · outbound

This paper cites an unresolved cited work.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-04T22:41:55.300466Z

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Observation 3086b5d0-0a4d-4bf9-958b-6df054e7ce45 · outbound

This paper cites Pascanu, T.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Pascanu, T

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.287220Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fb41bfe1-392d-4e5d-bfe8-ad4a052eea99 · outbound

This paper cites Bottou, Stochastic gradient learning in neural networks, in: Proceedings of Neuro-N ˆımes 91, EC2, Nimes, France, 1991.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Bottou, Stochastic gradient learning in neural networks, in: Proceedings of Neuro-N ˆımes 91, EC2, Nimes, France, 1991

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.274403Z

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Observation aca58a01-12d9-4820-ae54-59189830d29d · outbound

This paper cites Qian, On the momentum term in gradient descent learning algorithms, Neural Netw.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Qian, On the momentum term in gradient descent learning algorithms, Neural Netw

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.630141Z

Source-reported events for the cited work

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Observation ba6d4e55-8502-4598-8592-2900ac43f262 · outbound

This paper cites an unresolved cited work.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-04T22:41:55.261224Z

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Observation eb24705b-4d83-43e9-ab9c-729b09418231 · outbound

This paper cites Mahdavimanshadi, M.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Mahdavimanshadi, M

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.637752Z

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Observation c6c37b5a-7675-4bd2-868f-0ab7b6df9dba · outbound

This paper cites Santos, T.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Santos, T

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.641554Z

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Observation 187e64c5-fb95-41e7-aaa4-de9f07357174 · outbound

This paper cites an unresolved cited work.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Unresolved cited work

Reference 12

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Observation da7585e2-1345-4584-bee6-dd6d3495c667 · outbound

This paper cites an unresolved cited work.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-04T22:41:55.249025Z

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Observation 0ebc22fb-4210-4651-a206-6bb473820f0f · outbound

This paper cites Martens, R.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Martens, R

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.235861Z

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Observation d8d19a26-cf42-46d7-b621-5c610da9d31e · outbound

This paper cites Ebadi, A.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Ebadi, A

Reference 15

Resolution: verified exact; doi, observed 2026-08-04T22:41:54.851416Z

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Observation e3df1ca4-3824-4d77-9ee7-fbd4a6079272 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Adam: A Method for Stochastic Optimization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.659796Z

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Observation b1fe86b1-748a-48d2-99c4-fd3aaaff8bb1 · outbound

This paper cites Duchi, E.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Duchi, E

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.222855Z

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Observation 2ecb06d9-eeab-43fd-9419-57b2ab5d1497 · outbound

This paper cites Tieleman, G.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Tieleman, G

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.210075Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 722ecbcf-3e80-46e3-84c9-e55213d1c77c · outbound

This paper cites Nesterov, A method for solving the convex programming problem with convergence rateo(1/k2), Doklady Akademii Nauk SSSR 269 (3) (1983) 543–547.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Nesterov, A method for solving the convex programming problem with convergence rateo(1/k2), Doklady Akademii Nauk SSSR 269 (3) (1983) 543–547

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.197114Z

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Observation a3bba823-5e49-49a7-b0c3-540077481be1 · outbound

This paper cites ADADELTA: An Adaptive Learning Rate Method.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions ADADELTA: An Adaptive Learning Rate Method

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.674720Z

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Unavailable: canonical work link unavailable.

Observation 4919d3d5-bffc-4311-a18d-1fe51eb6ef87 · outbound

This paper cites an unresolved cited work.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Unresolved cited work

Reference 21

Resolution: verified exact; doi, observed 2026-08-04T22:41:54.837682Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 185627e8-6e18-4c78-86c5-3aea45c443e9 · outbound

This paper cites an unresolved cited work.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Unresolved cited work

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.684266Z

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Unavailable: canonical work link unavailable.

Observation ad8f8516-20c8-4289-a0bd-df23128b6690 · outbound

This paper cites Gradient Centralization: A New Optimization Technique for Deep Neural Networks.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Gradient Centralization: A New Optimization Technique for Deep Neural Networks

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-04T22:41:54.995964Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 99e77d9f-bf42-4240-93d2-35a1d60074f0 · outbound

This paper cites Salimans, D.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Salimans, D

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.183629Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b4242110-55b1-42c2-913c-eecc532f887d · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.695633Z

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Observation 2b910e41-f09f-429c-9f93-7dc1aca7103d · outbound

This paper cites Santurkar, D.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Santurkar, D

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.171174Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 51d5871e-6242-48de-8fa2-0967c9074dce · outbound

This paper cites Ulyanov, A.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Ulyanov, A

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.703332Z

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Observation 630b2bb0-dd18-4f6d-b641-cd213be2dd57 · outbound

This paper cites Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.707450Z

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Unavailable: canonical work link unavailable.

Observation d0a99185-03ac-4d65-8099-9e7a30c5bab8 · outbound

This paper cites Layer Normalization.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Layer Normalization

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.711333Z

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Observation 664a8b7a-6330-4fc4-8790-8d77fcf88ff2 · outbound

This paper cites Group Normalization.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Group Normalization

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.715196Z

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Unavailable: canonical work link unavailable.

Observation 7a2e23b2-f1fa-4c3f-b59e-b737b9c542aa · outbound

This paper cites Micro-Batch Training with Batch-Channel Normalization and Weight Standardization.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Micro-Batch Training with Batch-Channel Normalization and Weight Standardization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.719204Z

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Observation c7a8f869-22ec-4dc9-bcfe-c81f2e39c15e · outbound

This paper cites Huang, X.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Huang, X

Reference 32

Resolution: verified exact; doi, observed 2026-08-04T22:41:54.805964Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 05e330b2-e541-4663-b946-8480f3e1f285 · outbound

This paper cites Sutskever, J.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Sutskever, J

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.157033Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3caa6e44-4d28-48d2-8da7-4384f3722c4a · outbound

This paper cites Pascanu, T.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Pascanu, T

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.142969Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3644ef98-811a-4db4-91ad-c1cddd97e568 · outbound

This paper cites an unresolved cited work.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-04T22:41:55.129715Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0bc66640-2799-4ddf-9bf0-8a92edc44a3e · outbound

This paper cites Adding Gradient Noise Improves Learning for Very Deep Networks.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Adding Gradient Noise Improves Learning for Very Deep Networks

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.738515Z

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Unavailable: canonical work link unavailable.

Observation e58433c8-8dce-4301-b566-04a154f32266 · outbound

This paper cites Alpaydin, C.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Alpaydin, C

Reference 37

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Unavailable: canonical work link unavailable.

Observation 47867ea4-ce32-4511-8229-4339443b9712 · outbound

This paper cites LeCun, C.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions LeCun, C

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.117301Z

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Observation 2f100049-0dec-44b1-830f-01272b0c1982 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.749813Z

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Unavailable: canonical work link unavailable.

Observation 70123dd2-7ac8-4372-aff6-bd7c2e309c9e · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:54.753829Z

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Unavailable: canonical work link unavailable.

Observation 605bbba2-74dc-485e-bcd3-0ab89bbc93e8 · outbound

This paper cites Courbariaux, Y.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Courbariaux, Y

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.104536Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ef315306-63c6-45a1-838d-1bd7936f4ccb · outbound

This paper cites Rastegari, V.

Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions Rastegari, V

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:41:55.091473Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

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