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Paper Citation Record · LEDGER

Learning in Deep Networks under Dale's Constraint

As of 13 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 0 inbound Pith citation observations for arXiv:2608.06963.

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

pith.paper-citation-record.v1
2608.06963 v1

Coverage vector

measured 100 of 300 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:39:42.655198Z

measured 100 of 100 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

100 of 300 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved90
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch9

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1d5c510b-755f-4574-a5d7-70bd583ff3ca · outbound

This paper cites Decoupling Gating from Linearity.

Learning in Deep Networks under Dale's Constraint Decoupling Gating from Linearity

Reference 1

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Observation 6af272ca-e730-4107-8f4e-d63e74667a92 · outbound

This paper cites Decoupled Weight Decay Regularization.

Learning in Deep Networks under Dale's Constraint Decoupled Weight Decay Regularization

Reference 2

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Observation 4cbd1539-adf0-45f0-adf9-fdb940dd8806 · outbound

This paper cites Nature neuroscience , volume=.

Learning in Deep Networks under Dale's Constraint Nature neuroscience , volume=

Reference 3

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Observation 18aae71b-8c00-4d0e-8c6f-a0788df8594e · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Learning in Deep Networks under Dale's Constraint Advances in Neural Information Processing Systems , volume=

Reference 4

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Observation f60b2705-ee67-4561-8c10-ca32de675e70 · outbound

This paper cites Net2Brain: A Toolbox to compare artificial vision models with human brain responses.

Learning in Deep Networks under Dale's Constraint Net2Brain: A Toolbox to compare artificial vision models with human brain responses

Reference 5

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Observation 5d8e4f4a-2b62-40d1-bde8-623dc264734e · outbound

This paper cites PLoS computational biology , volume=.

Learning in Deep Networks under Dale's Constraint PLoS computational biology , volume=

Reference 6

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Observation da68c1e0-45bc-4c4f-a8cd-bc1237eb646b · outbound

This paper cites nature , volume=.

Learning in Deep Networks under Dale's Constraint nature , volume=

Reference 7

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Observation b8471ec7-e0ec-4ca5-9482-58a576f8b1d3 · outbound

This paper cites CS 231N , volume=.

Learning in Deep Networks under Dale's Constraint CS 231N , volume=

Reference 8

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Observation f7eca98c-2af2-4f62-83af-77d8dbbf352a · outbound

This paper cites Disordered systems and biological organization , pages=.

Learning in Deep Networks under Dale's Constraint Disordered systems and biological organization , pages=

Reference 9

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Observation 6a6bf7bf-dd2b-493f-8d03-10ec454fb24d · outbound

This paper cites Joint european conference on machine learning and knowledge discovery in databases , pages=.

Learning in Deep Networks under Dale's Constraint Joint european conference on machine learning and knowledge discovery in databases , pages=

Reference 10

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source=arxiv_source observed=2026-08-10T17:39:42.193598Z digest=sha256:e6f5b0f21d684a33fcb3fa658cdd90d362e7b1d4b502f2a70cbf650609967b19

Observation 84f875ab-1d2a-4e44-bd0e-26c491e99187 · outbound

This paper cites GAIT-prop: A biologically plausible learning rule derived from backpropagation of error.

Learning in Deep Networks under Dale's Constraint GAIT-prop: A biologically plausible learning rule derived from backpropagation of error

Reference 11

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Observation 8a157f75-802e-4280-b1ec-919b75452a65 · outbound

This paper cites Proceedings of the national academy of sciences , volume=.

Learning in Deep Networks under Dale's Constraint Proceedings of the national academy of sciences , volume=

Reference 12

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Observation 183bc3c9-46c6-4d12-a803-4b1f729a5322 · outbound

This paper cites Early Inference in Energy-Based Models Approximates Back-Propagation.

Learning in Deep Networks under Dale's Constraint Early Inference in Energy-Based Models Approximates Back-Propagation

Reference 13

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Observation 79c3c4cd-b1f0-4d0f-8e10-10c25770b235 · outbound

This paper cites Frontiers in computational neuroscience , volume=.

Learning in Deep Networks under Dale's Constraint Frontiers in computational neuroscience , volume=

Reference 14

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source=arxiv_source observed=2026-08-10T17:39:42.216489Z digest=sha256:a29dc7b4176e96016f84b085e2523c2ab581820149eb043fbfe0686897f3b782

Observation 0fe6edfe-feb1-4583-9e2c-66f20182dadd · outbound

This paper cites Frontiers in neuroscience , volume=.

Learning in Deep Networks under Dale's Constraint Frontiers in neuroscience , volume=

Reference 15

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Observation a1c4ffb2-1988-4436-a76b-16624afa4eb0 · outbound

This paper cites Annals of the New York Academy of Sciences , volume=.

Learning in Deep Networks under Dale's Constraint Annals of the New York Academy of Sciences , volume=

Reference 16

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Observation cdee25b3-7a5e-44e3-92ea-5908ec5dc1a3 · outbound

This paper cites Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning.

Learning in Deep Networks under Dale's Constraint Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning

Reference 17

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Observation 76697e78-44aa-4448-86e3-41eddca46433 · outbound

This paper cites Neural computation , volume=.

Learning in Deep Networks under Dale's Constraint Neural computation , volume=

Reference 18

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Observation 94dd01dd-5d3e-49b7-82b2-ffcc69c8abcd · outbound

This paper cites Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain.

Learning in Deep Networks under Dale's Constraint Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain

Reference 19

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local_arxiv, observed 2026-08-10T17:39:45.010145Z

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Observation 62863c1d-ba9b-4f29-bd6f-4cdd2fda3463 · outbound

This paper cites Proceedings of the IEEE , volume=.

Learning in Deep Networks under Dale's Constraint Proceedings of the IEEE , volume=

Reference 20

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Observation a5fd7897-950d-4651-af10-759fe2afb45c · outbound

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

Learning in Deep Networks under Dale's Constraint Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 21

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Observation afdb5c68-4fee-460c-8c1f-3f9586819ae0 · outbound

This paper cites The journal of machine learning research , volume=.

Learning in Deep Networks under Dale's Constraint The journal of machine learning research , volume=

Reference 22

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source=arxiv_source observed=2026-08-10T17:39:42.259745Z digest=sha256:420fc77de34c13477e231bcfd411b9ce16bb6cdd9de0f80a9cda13bda7cfc57a

Observation d715093a-f26f-4f5a-afe0-0855cf923308 · outbound

This paper cites Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs.

Learning in Deep Networks under Dale's Constraint Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs

Reference 23

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Observation ba5820c4-d10e-41f3-96f5-e9d63340a259 · outbound

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Learning in Deep Networks under Dale's Constraint The Eleventh International Conference on Learning Representations , year=

Reference 24

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Observation c9ca4f47-ae3e-4a5a-95e2-ff877dbf562a · outbound

This paper cites Meta-Learning Deep Energy-Based Memory Models.

Learning in Deep Networks under Dale's Constraint Meta-Learning Deep Energy-Based Memory Models

Reference 25

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Observation 37be3224-b3b8-43b7-87f7-f864e8f608f9 · outbound

This paper cites 2009 , publisher=.

Learning in Deep Networks under Dale's Constraint 2009 , publisher=

Reference 26

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Observation 69dbc75a-a114-4c22-82f0-a4f140f1197a · outbound

This paper cites PLoS computational biology , volume=.

Learning in Deep Networks under Dale's Constraint PLoS computational biology , volume=

Reference 27

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Observation 82a6a894-1ad4-4c58-b697-b5ec4045405a · outbound

This paper cites Journal of Neuroscience , volume=.

Learning in Deep Networks under Dale's Constraint Journal of Neuroscience , volume=

Reference 28

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Observation e76e78d8-c383-4d6a-a676-d88898dff612 · outbound

This paper cites Annual review of vision science , volume=.

Learning in Deep Networks under Dale's Constraint Annual review of vision science , volume=

Reference 29

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Observation 6383d178-90a6-4f24-9540-ef08145d18e8 · outbound

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Learning in Deep Networks under Dale's Constraint 2005 , publisher=

Reference 30

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Observation 8a11aa19-9949-45e8-bd5c-c7f5f7360895 · outbound

This paper cites Science , volume=.

Learning in Deep Networks under Dale's Constraint Science , volume=

Reference 31

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Observation 33137e59-1d7b-42a9-8e6e-a64cf89ff723 · outbound

This paper cites Nature , volume=.

Learning in Deep Networks under Dale's Constraint Nature , volume=

Reference 32

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Observation 2a47de2f-81a7-45cb-b56d-6320120c7803 · outbound

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Learning in Deep Networks under Dale's Constraint Image interpretation by iterative bottom-up top-down processing

Reference 33

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Observation 295817c0-6d0f-4300-a10b-65a4733bfa10 · outbound

This paper cites Proceedings of the National Academy of Sciences , volume=.

Learning in Deep Networks under Dale's Constraint Proceedings of the National Academy of Sciences , volume=

Reference 34

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Observation 5ac65866-05a8-40e8-ac2f-1d7682be4e7e · outbound

This paper cites Proceedings of the National Academy of Sciences , volume=.

Learning in Deep Networks under Dale's Constraint Proceedings of the National Academy of Sciences , volume=

Reference 35

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Observation b48667c8-64cf-48b9-a255-9e79c87a9017 · outbound

This paper cites Journal of Comparative Neurology , volume=.

Learning in Deep Networks under Dale's Constraint Journal of Comparative Neurology , volume=

Reference 36

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Observation 6dffea61-d5b9-430a-9a8f-d45d9a419edc · outbound

This paper cites nature , volume=.

Learning in Deep Networks under Dale's Constraint nature , volume=

Reference 37

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Observation 7505169f-4ce0-4eda-b0cd-e3eb9e858bee · outbound

This paper cites Neural networks , volume=.

Learning in Deep Networks under Dale's Constraint Neural networks , volume=

Reference 38

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Observation 0ccdce2a-3cd5-4b93-b905-90db3aa93a40 · outbound

This paper cites , author=.

Learning in Deep Networks under Dale's Constraint , author=

Reference 39

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Observation 459d545c-ff7b-4666-aebd-90651f53b285 · outbound

This paper cites Cognitive science , volume=.

Learning in Deep Networks under Dale's Constraint Cognitive science , volume=

Reference 40

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Observation a057e7fc-a6e2-4e06-8893-8259f1517882 · outbound

This paper cites Proceedings of the IEEE conference on computer vision and pattern recognition , pages=.

Learning in Deep Networks under Dale's Constraint Proceedings of the IEEE conference on computer vision and pattern recognition , pages=

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Observation 03cd11bf-320c-48e5-97ea-9a8b976063e1 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Learning in Deep Networks under Dale's Constraint An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

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Observation f844fb07-3582-4819-97e9-45256d5742e7 · outbound

This paper cites International conference on machine learning , pages=.

Learning in Deep Networks under Dale's Constraint International conference on machine learning , pages=

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source=arxiv_source observed=2026-08-10T17:39:42.371038Z digest=sha256:7457ef7c9ff3ed4d54412d70c72e6325dc6737892fb2e9adc45d7d953688b134

Observation 0554194c-eca0-4746-bd95-27c38ceec245 · outbound

This paper cites Visual Instruction Tuning.

Learning in Deep Networks under Dale's Constraint Visual Instruction Tuning

Reference 44

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source=arxiv_source observed=2026-08-10T17:39:42.376017Z digest=sha256:1b51af63acb8d7196f6ad261828ebe6964af5df4da861b2e1e7fb68e04747edf

Observation 6a76c6a6-5aad-404b-815f-b9e11747b0af · outbound

This paper cites BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models.

Learning in Deep Networks under Dale's Constraint BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

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source=arxiv_source observed=2026-08-10T17:39:42.380799Z digest=sha256:6ae4cf638ea6743a710465a573cfd9bb5f99011605bf3e622b742f896f18c9fb

Observation 67ea0a1c-7042-4e78-b834-d65abdf1319c · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Learning in Deep Networks under Dale's Constraint Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

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source=arxiv_source observed=2026-08-10T17:39:42.386008Z digest=sha256:30ed17bbd24d87f46262a70aff6139fdd21e11fbd7388e4e8ca53ed884e412d3

Observation 6c22f09e-8eff-48b5-ac04-dae50977c9b9 · outbound

This paper cites Proceedings of the thirteenth international conference on artificial intelligence and statistics , pages=.

Learning in Deep Networks under Dale's Constraint Proceedings of the thirteenth international conference on artificial intelligence and statistics , pages=

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Observation 7e785be0-beaf-41e1-9adf-8bc34ad862b5 · outbound

This paper cites International conference on machine learning , pages=.

Learning in Deep Networks under Dale's Constraint International conference on machine learning , pages=

Reference 48

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source=arxiv_source observed=2026-08-10T17:39:42.396931Z digest=sha256:ee9a68316c9422c325768f044836c0083df4fbc52a0701949828cfca762964c2

Observation f2119139-241a-4653-8087-5dd4084b96de · outbound

This paper cites IEEE transactions on Information Theory , volume=.

Learning in Deep Networks under Dale's Constraint IEEE transactions on Information Theory , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.401503Z digest=sha256:c50acf4fd687ec72e6e4ad7bbe5ac26f2a808e5dd79fbb6d79999b50caceed31

Observation a872a66c-6811-4e6e-9aba-77049c4b1ce8 · outbound

This paper cites Neural computation , volume=.

Learning in Deep Networks under Dale's Constraint Neural computation , volume=

Reference 50

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source=arxiv_source observed=2026-08-10T17:39:42.406752Z digest=sha256:865b6fc1f3f6d3f156aa94a9b949c2ed7164aace613f0d64706e170cd978c165

Observation b2e4f3eb-815e-4175-ba52-6204e785fe59 · outbound

This paper cites Proceedings of the National Academy of Sciences , volume=.

Learning in Deep Networks under Dale's Constraint Proceedings of the National Academy of Sciences , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.411532Z digest=sha256:ba5d92ba4252c271b62b12cd22243f8496fe76d1ba9e3a4be8bdbfcbce7d6955

Observation 0b7099ac-1daa-419a-9d06-38fd5dffac55 · outbound

This paper cites Proceedings of the national academy of sciences , volume=.

Learning in Deep Networks under Dale's Constraint Proceedings of the national academy of sciences , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.416442Z digest=sha256:0f72b9b4ee7468fdb0863f19ef5418d4bc7e0aa7c071bab5460777c7121de385

Observation 396d817d-d2f9-4764-8ecb-131035f9f5d7 · outbound

This paper cites Science , volume=.

Learning in Deep Networks under Dale's Constraint Science , volume=

Reference 53

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source=arxiv_source observed=2026-08-10T17:39:42.421176Z digest=sha256:88572a68d634e9e98ce7817643c730acc94e4c406dd3e873895ef5fc2b680ff6

Observation 19df9a2d-8d6a-4e65-9475-89c6bfcaef2d · outbound

This paper cites Nature communications , volume=.

Learning in Deep Networks under Dale's Constraint Nature communications , volume=

Reference 54

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source=arxiv_source observed=2026-08-10T17:39:42.426318Z digest=sha256:f6d2c6f3e9534c1522b703768ff22098102f541a555be383850b1aab7447ad12

Observation bb6a33d6-fb54-4d99-91b4-030ed3b87a9f · outbound

This paper cites Deep Learning without Weight Transport.

Learning in Deep Networks under Dale's Constraint Deep Learning without Weight Transport

Reference 55

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local_arxiv, observed 2026-08-10T17:39:44.844033Z

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source=arxiv_source observed=2026-08-10T17:39:42.431307Z digest=sha256:38fc3769c2786ae5c611df6c4fdfc1952d312e4a3dcfe94824fef735cfa8ff31

Observation d6591ead-1e8e-4100-95c3-5cad65321ace · outbound

This paper cites Journal of mathematical biology , volume=.

Learning in Deep Networks under Dale's Constraint Journal of mathematical biology , volume=

Reference 56

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source=arxiv_source observed=2026-08-10T17:39:42.436400Z digest=sha256:5e7188a103a10b4decf2789222b236d972227f7ab8e4c58a7e3712343fa98f2f

Observation 1ffd26b7-9562-469b-aa66-4ed3af5ccfd5 · outbound

This paper cites Feedback alignment in deep convolutional networks.

Learning in Deep Networks under Dale's Constraint Feedback alignment in deep convolutional networks

Reference 57

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source=arxiv_source observed=2026-08-10T17:39:42.441159Z digest=sha256:a32e14cf8eadd7b522fe00e202a38a4dbaed0b738d00d14fac50ef91de7babc6

Observation 6b28bf87-45b9-45c2-88ab-66abc4c7b6ea · outbound

This paper cites Biologically-plausible learning algorithms can scale to large datasets.

Learning in Deep Networks under Dale's Constraint Biologically-plausible learning algorithms can scale to large datasets

Reference 58

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source=arxiv_source observed=2026-08-10T17:39:42.446510Z digest=sha256:d65ad2da019743d8fdc38fbaf7252fb50b5a1987cdb3e0062c310f34fbe55099

Observation 18dcd67d-74d5-4b8b-ae7d-a90287f984b6 · outbound

This paper cites Self-Assembly of a Biologically Plausible Learning Circuit.

Learning in Deep Networks under Dale's Constraint Self-Assembly of a Biologically Plausible Learning Circuit

Reference 59

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local_arxiv, observed 2026-08-10T17:39:44.789870Z

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source=arxiv_source observed=2026-08-10T17:39:42.451916Z digest=sha256:ca6c5eab31c7dfa84355f7c1946c67dc34c1c23baff411495a2c84a6c8436be5

Observation 5e6e0de6-2793-432c-8a48-24e5e8525dc2 · outbound

This paper cites Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94) , volume=.

Learning in Deep Networks under Dale's Constraint Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94) , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.456945Z digest=sha256:b42b77bded268f771df2839b8ce15818eedc1eb098e02034eeff77cf119b86b9

Observation 44b5b0c5-3049-4d31-99d7-0fb7a2049772 · outbound

This paper cites Attention Is All You Need.

Learning in Deep Networks under Dale's Constraint Attention Is All You Need

Reference 61

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source=arxiv_source observed=2026-08-10T17:39:42.462045Z digest=sha256:992b5aee44135aa67a948b2e1a1f0b51542007cd72ee746f5be59596a0278a44

Observation 891b3e14-f56f-4075-a94d-dcc96b23d25a · outbound

This paper cites Auto-Encoding Variational Bayes.

Learning in Deep Networks under Dale's Constraint Auto-Encoding Variational Bayes

Reference 62

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source=arxiv_source observed=2026-08-10T17:39:42.467128Z digest=sha256:5796b2cf71efd8f3714e98bea0d5afc6f8f1c578c0ec6ced9b75aca2e8765f1e

Observation c8997dc6-57aa-4c78-883c-14a299c25e3e · outbound

This paper cites Processes of change in brain and cognitive development: Attention and performance xxi , volume=.

Learning in Deep Networks under Dale's Constraint Processes of change in brain and cognitive development: Attention and performance xxi , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.472378Z digest=sha256:6cf76755d69fbe214c2e0cab892aa127ebba9186abe8c9f98bca0bd420ac97dc

Observation dcae5c49-40b4-439a-8b96-49eed4e0c789 · outbound

This paper cites Advances in neural information processing systems , volume=.

Learning in Deep Networks under Dale's Constraint Advances in neural information processing systems , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.477127Z digest=sha256:af6fe17df16663dd37539364404e3402c00d1febef2f9bec89dce7d7488c9109

Observation e15df218-3c2e-4f00-8732-5ae31d4a65c5 · outbound

This paper cites Advances in neural information processing systems , volume=.

Learning in Deep Networks under Dale's Constraint Advances in neural information processing systems , volume=

Reference 65

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source=arxiv_source observed=2026-08-10T17:39:42.481976Z digest=sha256:53aab7b8f0b0f356a647eecd132ce45a5a6af50670639fd30705c09d7ca39486

Observation 81597f16-b308-481a-a78c-fe8f0f679165 · outbound

This paper cites International Conference on Medical image computing and computer-assisted intervention , pages=.

Learning in Deep Networks under Dale's Constraint International Conference on Medical image computing and computer-assisted intervention , pages=

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source=arxiv_source observed=2026-08-10T17:39:42.487094Z digest=sha256:b40eaf21dcf72da7bf204a854b6a7f43ef3380c539442aef78e85a007f4d8f0d

Observation 15abd7e8-394d-40e4-9eef-91fadedad7a9 · outbound

This paper cites Deep learning in medical image analysis and multimodal learning for clinical decision support , pages=.

Learning in Deep Networks under Dale's Constraint Deep learning in medical image analysis and multimodal learning for clinical decision support , pages=

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source=arxiv_source observed=2026-08-10T17:39:42.491943Z digest=sha256:6449f30a07427e68d324ee758b479766e54d73fbc71a0326158e3eafa3f34684

Observation 92409fca-1dc4-494c-9d08-9a74fa6d3c44 · outbound

This paper cites ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=.

Learning in Deep Networks under Dale's Constraint ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=

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source=arxiv_source observed=2026-08-10T17:39:42.496882Z digest=sha256:7ffb57ab76e9e780d207d914f8254263e7802937855a2a26c09330fbc32461cf

Observation a7728f29-a60d-4682-a6b6-1cda031e203e · outbound

This paper cites Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation.

Learning in Deep Networks under Dale's Constraint Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation

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source=arxiv_source observed=2026-08-10T17:39:42.501818Z digest=sha256:be00f75439443d854bb90a835b56448fccf9ee3a620fa8b39a0f839723fbc1d8

Observation fc130a08-7002-4297-bcc3-d1646a891751 · outbound

This paper cites Neural computation , volume=.

Learning in Deep Networks under Dale's Constraint Neural computation , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.506753Z digest=sha256:6053a84130aa746e6ae49c107aab266a67288a799a24416152716190ad64555a

Observation 2c257740-e489-4f87-b27a-5b9081d39c0c · outbound

This paper cites IEEE transactions on medical imaging , volume=.

Learning in Deep Networks under Dale's Constraint IEEE transactions on medical imaging , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.511909Z digest=sha256:a0718039c07a252a0cf473d46e60812cc1468c3209be07d809bde7440c67da59

Observation cde12b90-ea4e-4bfa-8fa6-8945257eecc1 · outbound

This paper cites NVAE: A Deep Hierarchical Variational Autoencoder.

Learning in Deep Networks under Dale's Constraint NVAE: A Deep Hierarchical Variational Autoencoder

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source=arxiv_source observed=2026-08-10T17:39:42.516814Z digest=sha256:6f88b2c76adad15a5a12d73e1d79293be8e0f54ee6568dfea2d5fa471964476f

Observation 759f0bba-ee84-465e-883e-11b39cc7872b · outbound

This paper cites AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence.

Learning in Deep Networks under Dale's Constraint AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence

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source=arxiv_source observed=2026-08-10T17:39:42.521737Z digest=sha256:3d77c897aaae65761066a53ea636815880a0965feda94566e6143e9455fd9d82

Observation 3145468f-48b9-40fc-90cd-f0962e13e043 · outbound

This paper cites Humanities and Social Sciences Communications , volume=.

Learning in Deep Networks under Dale's Constraint Humanities and Social Sciences Communications , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.526921Z digest=sha256:09c9775c58940bcf16a77ee2be48f4394c4861fb628d0deda1d2b55ae1d86c5f

Observation a557f94f-1281-4a92-aae8-e62a25c1a7ac · outbound

This paper cites "Weak AI" is Likely to Never Become "Strong AI", So What is its Greatest Value for us?.

Learning in Deep Networks under Dale's Constraint "Weak AI" is Likely to Never Become "Strong AI", So What is its Greatest Value for us?

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local_arxiv, observed 2026-08-10T17:39:44.688175Z

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.

source=arxiv_source observed=2026-08-10T17:39:42.531668Z digest=sha256:f8e0853fd7b4f68c1999e37acf90757ef732fef30209b1fd74fd1e6bbe534d6c

Observation 1b0a5346-0b91-43b1-a9cc-f0f5a1c2d83d · outbound

This paper cites Neuron , volume=.

Learning in Deep Networks under Dale's Constraint Neuron , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.536624Z digest=sha256:f55519b357428cb20a6a511c435c6a4b0f9afad26d842f04f2726b823e9b7e68

Observation 1d33096f-c5ff-44f0-84ce-1ec3547b2f4a · outbound

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

Learning in Deep Networks under Dale's Constraint How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation

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source=arxiv_source observed=2026-08-10T17:39:42.541760Z digest=sha256:ac6d2f4c1c3903ba604335a3aae06f827937dcf6bb52254fea9b9581859f6365

Observation 7cfd7f07-ff8f-4ab6-8266-a66800d33580 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Learning in Deep Networks under Dale's Constraint Advances in Neural Information Processing Systems , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.546792Z digest=sha256:a753478901e456be70770deca4078f30014408cad7de13d624cbab366985b2a0

Observation aba72cb0-ca0c-490b-a788-e90ed7b60366 · outbound

This paper cites Nature Reviews Neuroscience , volume=.

Learning in Deep Networks under Dale's Constraint Nature Reviews Neuroscience , volume=

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source=arxiv_source observed=2026-08-10T17:39:42.551862Z digest=sha256:f35a1746f9cb300af2b2400128f8b47117011594f8f6e36ea29d13b633f38116

Observation 4d67b833-585a-47a5-8b48-a7552448ac7b · outbound

This paper cites International Conference on Machine Learning , pages=.

Learning in Deep Networks under Dale's Constraint International Conference on Machine Learning , pages=

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source=arxiv_source observed=2026-08-10T17:39:42.556505Z digest=sha256:f510e4260c2b0d1c7d040f8087a736fe7128115d8d6609b2af4e138a1e5c12c0

Observation 9edab21d-701e-4c68-ad92-3d6101838755 · outbound

This paper cites , author=.

Learning in Deep Networks under Dale's Constraint , author=

Reference 81

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source=arxiv_source observed=2026-08-10T17:39:42.561393Z digest=sha256:99e1c107de3c098864b5db361351d3bd859e2ace73060d9213cdc73bfe95ff76

Observation 9eec350d-e149-413d-be20-0f2c4f31716a · outbound

This paper cites Target Propagation via Regularized Inversion.

Learning in Deep Networks under Dale's Constraint Target Propagation via Regularized Inversion

Reference 82

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local_arxiv, observed 2026-08-10T17:39:44.647264Z

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.

source=arxiv_source observed=2026-08-10T17:39:42.566090Z digest=sha256:743a8512c29b883fd64d076a1a16a8e600c939c382e461372ed22843cddcd595

Observation d3c002be-e7c8-4842-b90a-53318598a8c0 · outbound

This paper cites The Neuroscientist , volume=.

Learning in Deep Networks under Dale's Constraint The Neuroscientist , volume=

Reference 83

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source=arxiv_source observed=2026-08-10T17:39:42.570994Z digest=sha256:2ecd88adfb32825eeefaa313661a2f5887f42e2f6b4bc955ad20d020986f4321

Observation 3eb63a3a-d5a0-4761-8051-d4d8d4923b5d · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Learning in Deep Networks under Dale's Constraint Advances in Neural Information Processing Systems , volume=

Reference 84

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no resolver link, observed 2026-08-10T17:39:42.576384Z

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source=arxiv_source observed=2026-08-10T17:39:42.576384Z digest=sha256:ef73cabc612dc1c42b0a4660be3966099768c61789ee431c9f88a1bcc79230c6

Observation caccaf71-0181-4851-aa1b-56848b7b8333 · outbound

This paper cites 2021 IEEE International Conference on Image Processing (ICIP) , pages=.

Learning in Deep Networks under Dale's Constraint 2021 IEEE International Conference on Image Processing (ICIP) , pages=

Reference 85

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source=arxiv_source observed=2026-08-10T17:39:42.581204Z digest=sha256:68ff1e9742d5248cd8f18b16cc4e5ee637abd604facfa381fa4982bb61bad283

Observation 92e98093-c70f-49ce-be47-66c2d1d44ccb · outbound

This paper cites Multi-Task Learning with Deep Neural Networks: A Survey.

Learning in Deep Networks under Dale's Constraint Multi-Task Learning with Deep Neural Networks: A Survey

Reference 86

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source=arxiv_source observed=2026-08-10T17:39:42.585945Z digest=sha256:459988a9e73e4a97008add606552d1267cc7072c9917ef72b31466f3749222dd

Observation c1ff7332-fa0e-4637-b158-1a2ad921a1f4 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Learning in Deep Networks under Dale's Constraint Advances in Neural Information Processing Systems , volume=

Reference 87

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no resolver link, observed 2026-08-10T17:39:42.590792Z

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source=arxiv_source observed=2026-08-10T17:39:42.590792Z digest=sha256:7e8cea534dd8732e566de1490d11f36dff48fd9d85b529de5ffbf8727eb23386

Observation aa9d8989-20ac-4fe2-9f59-82be6feea960 · outbound

This paper cites Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass.

Learning in Deep Networks under Dale's Constraint Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass

Reference 88

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no resolver link, observed 2026-08-10T17:39:42.596019Z

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source=arxiv_source observed=2026-08-10T17:39:42.596019Z digest=sha256:86256eaa04f0e4df78783d4d48152861bd3d30e023f5670fdac6d76c1ae58343

Observation 63d070e6-75de-4075-a1f6-37d1695a86a9 · outbound

This paper cites International Conference on Machine Learning , pages=.

Learning in Deep Networks under Dale's Constraint International Conference on Machine Learning , pages=

Reference 89

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no resolver link, observed 2026-08-10T17:39:42.600974Z

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source=arxiv_source observed=2026-08-10T17:39:42.600974Z digest=sha256:09802c106f05d046af45971f5a09fc27f30a5ebd4ff60ec598ef4da7c20d0589

Observation cdc85b13-375d-4c5d-943b-9514f25a0e04 · outbound

This paper cites Trends in cognitive sciences , volume=.

Learning in Deep Networks under Dale's Constraint Trends in cognitive sciences , volume=

Reference 90

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source=arxiv_source observed=2026-08-10T17:39:42.606053Z digest=sha256:51233841d983a892bae36593eb5cfbac0e22c065926e3323acb276a6ae1f6adb

Observation 7fe4c10f-6627-4bc8-ae7c-96acc420fcc2 · outbound

This paper cites International conference on machine learning , pages=.

Learning in Deep Networks under Dale's Constraint International conference on machine learning , pages=

Reference 91

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no resolver link, observed 2026-08-10T17:39:42.610694Z

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source=arxiv_source observed=2026-08-10T17:39:42.610694Z digest=sha256:e7256302015b70e262ec3f3962eaedcf3389211fd469d3201f194dda90623413

Observation d4e331df-f05f-4c72-8ec1-29e8dda3d67a · outbound

This paper cites Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning.

Learning in Deep Networks under Dale's Constraint Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 92

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no resolver link, observed 2026-08-10T17:39:42.615518Z

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source=arxiv_source observed=2026-08-10T17:39:42.615518Z digest=sha256:1d65b9d4c23c349c25dd0ea5ab4686a8d6a506f9156fc7796a13143bcc228747

Observation dcc7c1d9-05a9-4b8f-a95e-edca40d4b6f5 · outbound

This paper cites Neuron , volume=.

Learning in Deep Networks under Dale's Constraint Neuron , volume=

Reference 93

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no resolver link, observed 2026-08-10T17:39:42.620378Z

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source=arxiv_source observed=2026-08-10T17:39:42.620378Z digest=sha256:27e710869776c59a53dc2c93eb0e55777656ee85fccaeb8b38bec7cb451ccf3d

Observation e5b15e56-97e0-438b-b3d2-c60d797e23fc · outbound

This paper cites A model for full local image interpretation.

Learning in Deep Networks under Dale's Constraint A model for full local image interpretation

Reference 94

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metadata mismatch
local_arxiv, observed 2026-08-10T17:39:44.575062Z

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.

source=arxiv_source observed=2026-08-10T17:39:42.625523Z digest=sha256:f403a3ec6c2a4d9d2b61444f8a8adb3ab2fba29a2b3cdd5ccc7e3190a1a846f4

Observation 205a7cbe-a743-4f07-bd31-f4eb3ab7940e · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

Learning in Deep Networks under Dale's Constraint Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 95

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no resolver link, observed 2026-08-10T17:39:42.630281Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-10T17:39:42.630281Z digest=sha256:c58bcf40893c3bc0562505297b8ed593983c4b7a3d109190dc82777d97138907

Observation 5b311aa9-a47f-433c-9054-0a051c90620d · outbound

This paper cites Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , pages=.

Learning in Deep Networks under Dale's Constraint Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , pages=

Reference 96

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no resolver link, observed 2026-08-10T17:39:42.635356Z

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source=arxiv_source observed=2026-08-10T17:39:42.635356Z digest=sha256:1f35aa0d8c0a05569819359e28513f2209f2975ed50fc8d4bec74928cbc2aeb8

Observation 22f2e46c-56df-4844-88f1-c515be4b6d2d · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

Learning in Deep Networks under Dale's Constraint Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 97

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no resolver link, observed 2026-08-10T17:39:42.640047Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-10T17:39:42.640047Z digest=sha256:f341ca9901398de9567745bee97920dd393229ae2c315b7d4e1275aa2ee6c631

Observation 5417b479-712a-4dfe-ad31-9663b42ba9dd · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

Learning in Deep Networks under Dale's Constraint Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 98

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no resolver link, observed 2026-08-10T17:39:42.645667Z

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source=arxiv_source observed=2026-08-10T17:39:42.645667Z digest=sha256:1ab1d3d3a9f7834d471e1e8b1983feebb0dd5137aab2d5be4ab2b64705a56734

Observation f7629a35-8633-4067-b6bd-a3759e34786f · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

Learning in Deep Networks under Dale's Constraint Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 99

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no resolver link, observed 2026-08-10T17:39:42.650189Z

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source=arxiv_source observed=2026-08-10T17:39:42.650189Z digest=sha256:6c03fe9b13cbcb049a4804881766d02994bf30f3a413e00540e4b027bf7516dd

Observation 26ac4b7b-184f-46d5-a99b-399700d1ed43 · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.

Learning in Deep Networks under Dale's Constraint Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

Reference 100

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no resolver link, observed 2026-08-10T17:39:42.655198Z

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source=arxiv_source observed=2026-08-10T17:39:42.655198Z digest=sha256:c34488abc492a4ceae98de6bac53707f6c6193325efb355b8a403010cdf39ef1

Pith citing papers

No inbound Pith citation observations are available.