Paper Citation Record · LEDGER

Sign-Symmetry Learning Rules are Robust Fine-Tuners

As of 13 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2502.05925.

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

pith.paper-citation-record.v1
2502.05925 v2

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:25:06.411860Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

50 of 50 outbound references displayed

verified exact2
verified fuzzy22
unresolved25
parse uncertain0
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External citation measurements

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Outbound references

Observation 2621a9d0-3b8a-4ec5-8e83-4b02ac2d91b0 · outbound

This paper cites write newline.

Sign-Symmetry Learning Rules are Robust Fine-Tuners write newline

Reference 1

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Observation 3c29aade-d5c0-4688-9d96-a7f6980fca63 · outbound

This paper cites Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples

Reference 2

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Observation 7fe37da2-ccff-48a0-9991-152e5eebab31 · outbound

This paper cites E., and Lillicrap, T.

Sign-Symmetry Learning Rules are Robust Fine-Tuners E., and Lillicrap, T

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:25:08.519840Z

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Observation 51ba6a82-bb8b-40cc-906f-7928c52a5c45 · outbound

This paper cites How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation.

Sign-Symmetry Learning Rules are Robust Fine-Tuners How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation

Reference 4

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Observation 3863855a-8e89-49fc-9d73-28cf325e7f79 · outbound

This paper cites Leveraging High-Resolution Features for Improved Deep Hashing-based Image Retrieval.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Leveraging High-Resolution Features for Improved Deep Hashing-based Image Retrieval

Reference 5

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Observation 98b607f6-2c66-4884-96e6-5b772e461b37 · outbound

This paper cites an unresolved cited work.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Unresolved cited work

Reference 6

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Observation e90425e3-4ddb-4207-9510-ed1a18fe3237 · outbound

This paper cites Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

Reference 7

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Observation 203c20cf-5653-4e63-aed1-f9fa2565636d · outbound

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Sign-Symmetry Learning Rules are Robust Fine-Tuners Unresolved cited work

Reference 8

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Observation 43a45781-75d2-4792-aa8b-b15ddd375e62 · outbound

This paper cites On Evaluating Adversarial Robustness.

Sign-Symmetry Learning Rules are Robust Fine-Tuners On Evaluating Adversarial Robustness

Reference 9

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Observation 93eb4d83-a219-4c3a-b7c7-2951f43c86ea · outbound

This paper cites HopSkipJumpAttack: A Query-Efficient Decision-Based Attack.

Sign-Symmetry Learning Rules are Robust Fine-Tuners HopSkipJumpAttack: A Query-Efficient Decision-Based Attack

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T17:25:05.636533Z

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Observation c89b116b-0ff7-464a-b124-fd8205995723 · outbound

This paper cites Nus-wide: a real-world web image database from national university of singapore.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Nus-wide: a real-world web image database from national university of singapore

Reference 11

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Observation e8a3ac2e-4a5e-4292-90db-514a7fcc088e · outbound

This paper cites The recent excitement about neural networks.

Sign-Symmetry Learning Rules are Robust Fine-Tuners The recent excitement about neural networks

Reference 12

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Observation cdae5c37-4c44-461c-a3b1-04a04e566629 · outbound

This paper cites M., \'S wirszcz, G., Jaderberg, M., Osindero, S., Vinyals, O., and Kavukcuoglu, K.

Sign-Symmetry Learning Rules are Robust Fine-Tuners M., \'S wirszcz, G., Jaderberg, M., Osindero, S., Vinyals, O., and Kavukcuoglu, K

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:25:08.444745Z

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Observation b85e349a-f4e6-43c5-a522-cec7af03efc6 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Imagenet: A large-scale hierarchical image database

Reference 14

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Observation 537ad359-1bd8-44d7-ba38-12f383e740c9 · outbound

This paper cites and Liu, L.

Sign-Symmetry Learning Rules are Robust Fine-Tuners and Liu, L

Reference 15

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Observation daa7ea58-3b64-4def-b8e8-417ee8733eca · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Explaining and Harnessing Adversarial Examples

Reference 16

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Observation 92a6ccbf-1f98-481a-a57b-4032806f6912 · outbound

This paper cites Competitive learning: From interactive activation to adaptive resonance.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Competitive learning: From interactive activation to adaptive resonance

Reference 17

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Observation 818c60cc-1be4-4109-bbf0-864a517159c8 · outbound

This paper cites Deep residual learning for image recognition.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Deep residual learning for image recognition

Reference 18

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Observation 7a85bdf3-aaa1-44a0-b400-12c3369452ee · outbound

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Sign-Symmetry Learning Rules are Robust Fine-Tuners Unresolved cited work

Reference 19

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Observation 3fb6c985-69a0-4052-89f3-c05be1cc820d · outbound

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Sign-Symmetry Learning Rules are Robust Fine-Tuners Unresolved cited work

Reference 20

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Observation a7d22cba-9b31-4945-967e-144383468f6b · outbound

This paper cites An efficient supervised deep hashing method for image retrieval.

Sign-Symmetry Learning Rules are Robust Fine-Tuners An efficient supervised deep hashing method for image retrieval

Reference 21

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Observation 41b652b7-5f26-4a42-b6b5-89179658c1dd · outbound

This paper cites Learning multiple layers of features from tiny images.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Learning multiple layers of features from tiny images

Reference 22

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Observation 5a53992d-3564-4302-b933-16cc7ec328a3 · outbound

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Sign-Symmetry Learning Rules are Robust Fine-Tuners Unresolved cited work

Reference 23

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Observation 9a97f1e6-d7d5-443a-a3e9-8adb3e5b9623 · outbound

This paper cites Learning to solve the credit assignment problem.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Learning to solve the credit assignment problem

Reference 24

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Observation 29f38062-e98d-4a8d-a9f8-184ef89981cb · outbound

This paper cites Learning process in an asymmetric threshold network.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Learning process in an asymmetric threshold network

Reference 25

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Observation 5fabcda0-ad73-432b-b5a8-45b411acf1ca · outbound

This paper cites Difference target propagation.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Difference target propagation

Reference 26

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Observation 623cc750-1c66-4238-9f08-864312107383 · outbound

This paper cites How important is weight symmetry in backpropagation? In Proceedings of the AAAI Conference on Artificial Intelligence, volume 30, 2016.

Sign-Symmetry Learning Rules are Robust Fine-Tuners How important is weight symmetry in backpropagation? In Proceedings of the AAAI Conference on Artificial Intelligence, volume 30, 2016

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:25:07.724111Z

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Observation 4a99e0dc-af2b-4cd4-a9ec-50987f62f7f2 · outbound

This paper cites Random feedback weights support learning in deep neural networks.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Random feedback weights support learning in deep neural networks

Reference 28

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Observation b08b3fc6-f845-40c9-9b0a-73a14cbaa0e8 · outbound

This paper cites P., Cownden, D., Tweed, D.

Sign-Symmetry Learning Rules are Robust Fine-Tuners P., Cownden, D., Tweed, D

Reference 29

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Observation 2ecf3ade-acca-4068-aa86-49cc4493475d · outbound

This paper cites P., Santoro, A., Marris, L., Akerman, C.

Sign-Symmetry Learning Rules are Robust Fine-Tuners P., Santoro, A., Marris, L., Akerman, C

Reference 30

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Observation 8b11435f-e8be-49a8-bc83-e665637a203a · outbound

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Sign-Symmetry Learning Rules are Robust Fine-Tuners Unresolved cited work

Reference 31

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This paper cites A smart adversarial attack on deep hashing based image retrieval.

Sign-Symmetry Learning Rules are Robust Fine-Tuners A smart adversarial attack on deep hashing based image retrieval

Reference 32

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Sign-Symmetry Learning Rules are Robust Fine-Tuners Image retrieval algorithm based on locality-sensitive hash using convolutional neural network and attention mechanism

Reference 33

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Observation 19a20f6c-e9ca-4547-8243-4f45277b1ad3 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 34

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Observation 394e3d73-f472-4c85-9d45-33c8065cca1d · outbound

This paper cites Regulation of synaptic efficacy by coincidence of postsynaptic aps and epsps.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Regulation of synaptic efficacy by coincidence of postsynaptic aps and epsps

Reference 35

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Observation 760cc671-2b3a-436c-b2d8-6a30d735522f · outbound

This paper cites Foolbox: A Python toolbox to benchmark the robustness of machine learning models.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Foolbox: A Python toolbox to benchmark the robustness of machine learning models

Reference 36

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Sign-Symmetry Learning Rules are Robust Fine-Tuners E., Hinton, G

Reference 37

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Sign-Symmetry Learning Rules are Robust Fine-Tuners Unresolved cited work

Reference 38

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Observation 2865d608-8db5-4c8b-a5f4-87c4d7bbfca0 · outbound

This paper cites Deep Hashing via Householder Quantization.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Deep Hashing via Householder Quantization

Reference 39

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Observation 7e97f15f-87be-41a0-a463-c2dc77433be3 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 40

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Sign-Symmetry Learning Rules are Robust Fine-Tuners and Gupta, S

Reference 41

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Observation a76c3dfb-edbb-4c41-a3ba-01d4e5a98cc8 · outbound

This paper cites Intriguing properties of neural networks.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Intriguing properties of neural networks

Reference 42

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Sign-Symmetry Learning Rules are Robust Fine-Tuners Adversarial risk and the dangers of evaluating against weak attacks

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:25:07.545382Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 40adac44-4bd3-4c4b-8264-5b78aadb0fb1 · outbound

This paper cites R., Banburski, A., Pant, N., and Poggio, T.

Sign-Symmetry Learning Rules are Robust Fine-Tuners R., Banburski, A., Pant, N., and Poggio, T

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:25:07.500380Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d950f269-256b-4d39-84bc-83857bead333 · outbound

This paper cites Supervised hashing for image retrieval via image representation learning.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Supervised hashing for image retrieval via image representation learning

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:25:07.456173Z

Source-reported events for the cited work

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Observation 4422ad75-9dc6-4534-aa0b-8fd13fc2dc72 · outbound

This paper cites Hyp2 loss: Beyond hypersphere metric space for multi-label image retrieval.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Hyp2 loss: Beyond hypersphere metric space for multi-label image retrieval

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:25:07.357118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1c791c69-f72c-4779-8a0f-d7395fa41292 · outbound

This paper cites Adversarial examples for hamming space search.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Adversarial examples for hamming space search

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:25:07.220045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fe3bba60-6251-4410-addf-3123ee0677e7 · outbound

This paper cites Deep parameter-free attention hashing for image retrieval.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Deep parameter-free attention hashing for image retrieval

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:25:07.054826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 30dbbee4-27b9-45f1-9403-6bfc066c162a · outbound

This paper cites Semantic-aware adversarial training for reliable deep hashing retrieval.

Sign-Symmetry Learning Rules are Robust Fine-Tuners Semantic-aware adversarial training for reliable deep hashing retrieval

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:25:06.994829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 179a5900-1c36-4d05-909f-b0ab51a8d16f · outbound

This paper cites The Limitations of Adversarial Training and the Blind-Spot Attack.

Sign-Symmetry Learning Rules are Robust Fine-Tuners The Limitations of Adversarial Training and the Blind-Spot Attack

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-08T17:25:06.554102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.