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Paper Citation Record · LEDGER

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning

As of 9 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2512.18471.

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

pith.paper-citation-record.v1
2512.18471 v2

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T15:02:53.641160Z

measured 70 of 70 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 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

70 of 70 outbound references displayed

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External citation measurements

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Outbound references

Observation 87c359e7-fa03-4ae5-83f8-e96a7cfc49f0 · outbound

This paper cites Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition,

Reference 1

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Observation c916fa1a-fdb2-4067-9928-a02683f06eb7 · outbound

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The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Unresolved cited work

Reference 2

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Observation f389d9a2-3b33-4003-915e-48af6f8a5cdb · outbound

This paper cites Understanding machine learning: From theory to algorithms,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Understanding machine learning: From theory to algorithms,

Reference 3

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Observation 71a4810a-1077-4720-9510-f39dcea2ab8e · outbound

This paper cites Catastrophic interference in connection- ist networks: The sequential learning problem,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Catastrophic interference in connection- ist networks: The sequential learning problem,

Reference 4

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Observation 9307bb0d-1741-4777-8a79-90f4aa853915 · outbound

This paper cites Catastrophic forgetting in connectionist networks,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Catastrophic forgetting in connectionist networks,

Reference 5

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Observation 56225271-5d5f-413a-b527-58886acd1754 · outbound

This paper cites Continual lifelong learning with neural networks: A review,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Continual lifelong learning with neural networks: A review,

Reference 6

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Observation a0b74834-ff55-4200-b95b-c05d6fb76fc7 · outbound

This paper cites Buzs ´aki,Rhythms of the Brain.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Buzs ´aki,Rhythms of the Brain

Reference 7

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Observation 0e45a919-8399-4bbc-b865-81350111fa0c · outbound

This paper cites The columnar organization of the neocortex,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning The columnar organization of the neocortex,

Reference 8

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Observation 14cf011f-3ef2-4ccf-aa88-b0aaaef099ad · outbound

This paper cites A hierarchy of temporal receptive windows in human cortex,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning A hierarchy of temporal receptive windows in human cortex,

Reference 9

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Observation 0f707aa9-3979-4487-9630-b92fb8dbf247 · outbound

This paper cites The architecture of complexity,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning The architecture of complexity,

Reference 10

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Observation 8f8e7d39-c944-458f-a287-f202fddf36fb · outbound

This paper cites A global geometric framework for nonlinear dimensionality reduction,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning A global geometric framework for nonlinear dimensionality reduction,

Reference 11

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Observation a01f5611-fc4a-4806-9f92-8fd57b4a0129 · outbound

This paper cites Testing the manifold hypothesis,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Testing the manifold hypothesis,

Reference 12

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Observation f503b3fa-c357-45c9-9d9d-283b1f40eacd · outbound

This paper cites Gromov,Metric Structures for Riemannian and Non-Riemannian Spaces.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Gromov,Metric Structures for Riemannian and Non-Riemannian Spaces

Reference 13

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Observation e757a384-6989-4e5e-9fb2-def6b898e813 · outbound

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The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Unresolved cited work

Reference 14

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Observation e813f956-fa22-44ad-b324-fb8fc52392d9 · outbound

This paper cites Catastrophic forgetting, rehearsal and pseudorehearsal,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Catastrophic forgetting, rehearsal and pseudorehearsal,

Reference 15

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Observation 68f57b12-9e4c-409c-8ca8-a9c5ef5e9b45 · outbound

This paper cites Prioritized Experience Replay.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Prioritized Experience Replay

Reference 16

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Observation 31009171-07b8-4bb5-9d35-b3631d43058e · outbound

This paper cites Overcoming catas- trophic forgetting in neural networks,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Overcoming catas- trophic forgetting in neural networks,

Reference 17

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Observation 44e5c350-39cc-4f55-a7e7-dfeda3e0f1c1 · outbound

This paper cites Feudal reinforcement learning,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Feudal reinforcement learning,

Reference 18

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Observation 6c5fc5a4-0ff4-42a7-bddf-7368cbcabf39 · outbound

This paper cites Hierarchical reinforcement learning with the maxq value function decomposition,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Hierarchical reinforcement learning with the maxq value function decomposition,

Reference 19

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Observation bc1494ae-7d21-47f7-ab81-4c0c58900b84 · outbound

This paper cites Benefits of depth in neural networks,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Benefits of depth in neural networks,

Reference 20

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Observation 1fa681e0-2540-440a-8f31-5c17634dd878 · outbound

This paper cites Proto-value functions: A laplacian framework for learning representation and control in markov decision processes,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Proto-value functions: A laplacian framework for learning representation and control in markov decision processes,

Reference 21

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Observation 2bf48162-642f-48bd-b1e9-b673009cd650 · outbound

This paper cites A comprehensive survey of continual learning: Theory, method and application,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning A comprehensive survey of continual learning: Theory, method and application,

Reference 22

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Observation 034647c3-0fb5-4908-9941-0f7d7734da6b · outbound

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The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Unresolved cited work

Reference 23

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Observation 50f4a7f2-a14e-47de-b94a-47c1c99c2921 · outbound

This paper cites Vershynin,High-Dimensional Probability: An Introduction with Applications in Data Science.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Vershynin,High-Dimensional Probability: An Introduction with Applications in Data Science

Reference 24

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Observation bca98fb7-927d-4b46-b2cd-485870e54b2e · outbound

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The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Unresolved cited work

Reference 25

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Observation 30f50604-895c-4168-bead-705ef7e4d4e0 · outbound

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The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Unresolved cited work

Reference 26

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Observation 17566e0e-16fb-4b23-838e-096aeafd2856 · outbound

This paper cites Gromov,Metric Structures for Riemannian and Non-Riemannian Spaces.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Gromov,Metric Structures for Riemannian and Non-Riemannian Spaces

Reference 27

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Observation fa65b970-6400-43cc-b08c-8f371c1716a3 · outbound

This paper cites On the gromov–hausdorff distance,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning On the gromov–hausdorff distance,

Reference 28

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Observation d80f63a0-df53-4bb4-8948-83306d90f313 · outbound

This paper cites Diffusion maps,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Diffusion maps,

Reference 29

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Observation c0f8495a-86c5-4981-ab13-1d41f7bb8d71 · outbound

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The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Burago, Y

Reference 30

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Observation 54bfcaf5-3deb-4c37-9df3-3631c79ab88b · outbound

This paper cites The hippocampus as a cognitive graph.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning The hippocampus as a cognitive graph

Reference 31

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This paper cites Memory, navigation and theta rhythm in the hippocampal-entorhinal system,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Memory, navigation and theta rhythm in the hippocampal-entorhinal system,

Reference 32

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Observation 0480e7ca-db8f-41d4-b918-45125c48cee2 · outbound

This paper cites Simplified neuron model as a principal component analyzer,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Simplified neuron model as a principal component analyzer,

Reference 33

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Observation 5b3b11e1-e5bd-4822-8769-381467fadad4 · outbound

This paper cites Optimal unsupervised learning in a single-layer linear feedforward neural network,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Optimal unsupervised learning in a single-layer linear feedforward neural network,

Reference 34

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Observation 3f404564-2056-40ad-803c-a217e51704db · outbound

This paper cites Reactivation of hippocampal ensemble memories during sleep,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Reactivation of hippocampal ensemble memories during sleep,

Reference 35

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Observation 3d87dec5-1cbc-42fc-b857-f7be6f70b2fc · outbound

This paper cites Hierarchical process memory: memory as an integral component of information processing,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Hierarchical process memory: memory as an integral component of information processing,

Reference 36

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Observation 2ac6198b-0926-40e4-9d6f-d6726a829133 · outbound

This paper cites A continual learning survey: Defying forgetting in classification tasks,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning A continual learning survey: Defying forgetting in classification tasks,

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Observation b9459fe4-d97c-4889-9256-2a51c17d8ec4 · outbound

This paper cites The Homological Brain: Parity Principle and Amortized Inference.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning The Homological Brain: Parity Principle and Amortized Inference

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Observation 4bb05a04-f9cb-4c1e-b3aa-83e3f2db75ed · outbound

This paper cites Active inference: a process theory,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Active inference: a process theory,

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Observation b4becc62-f718-478f-ab94-dcce1afb04a9 · outbound

This paper cites Memory consolidation,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Memory consolidation,

Reference 40

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source=pdf_text observed=2026-08-03T15:02:50.564236Z digest=sha256:147fd44911d866d362c5fb6d5d1e0749a8ec29a32d1718422c23fa5cd8311f0e

Observation 7e21813f-afca-4a01-8905-1b9bc1da9a58 · outbound

This paper cites Relationships between nondeterministic and deterministic tape complexities,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Relationships between nondeterministic and deterministic tape complexities,

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source=pdf_text observed=2026-08-03T15:02:50.645587Z digest=sha256:a252d0b2b9bff3c9f24bf95e3a330bc72a5dce0a45f8d8bec48c9656e70eadf1

Observation ac3c856d-4dd8-4586-ae32-c1fa842e18fc · outbound

This paper cites Shawe-Taylor and N.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Shawe-Taylor and N

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source=pdf_text observed=2026-08-03T15:02:50.814298Z digest=sha256:243031d6ab457a0639a574296d44276dd9c7262a5f4684226b2c0ff22ed07156

Observation 5263b9b7-234d-48cb-a822-33f9ef80f2c7 · outbound

This paper cites Willard,General topology.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Willard,General topology

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source=pdf_text observed=2026-08-03T15:02:50.962435Z digest=sha256:768a3ea6980be7725db342542e2f9ca6bf098d338ea8c98e0a5890ba4e048b96

Observation 437e7f6f-2368-4011-acaa-95eab114fcbf · outbound

This paper cites Bellman,Dynamic Programming.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Bellman,Dynamic Programming

Reference 44

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source=pdf_text observed=2026-08-03T15:02:51.070727Z digest=sha256:ddce293e26d19004d39e1ec0c551906123fb880ff4d08d63e19f8c570ae5bcc2

Observation dd355730-2046-4025-96d0-3bc61206d3db · outbound

This paper cites The theta-gamma neural code,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning The theta-gamma neural code,

Reference 45

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source=pdf_text observed=2026-08-03T15:02:51.210170Z digest=sha256:170779fae13d87e0b2e9b179080205b6b42b1a4e6c38ece3f8fd8f30622fb528

Observation 968599b9-da6d-47a2-bc46-a5065be801c5 · outbound

This paper cites The hippocampo-neocortical dialogue,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning The hippocampo-neocortical dialogue,

Reference 46

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source=pdf_text observed=2026-08-03T15:02:51.286465Z digest=sha256:bb3591026c2f37b8b6e46397de325cee6d93372c4aa97c203dcbe073f1c3bae7

Observation 45591153-5370-4639-b4a9-67541276db72 · outbound

This paper cites Theory of Deep Learning III: explaining the non-overfitting puzzle.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Theory of Deep Learning III: explaining the non-overfitting puzzle

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source=pdf_text observed=2026-08-03T15:02:51.402132Z digest=sha256:4f955791237449834985e1b3d0d9ec1e9f550248a6ba0d55a3709833751a0952

Observation e6ccd7e4-c49e-49c5-b445-19ce51144afb · outbound

This paper cites Hatcher,Algebraic topology, 2005.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Hatcher,Algebraic topology, 2005

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source=pdf_text observed=2026-08-03T15:02:51.500247Z digest=sha256:621287aad3a9ea4d2e990a3a967d95f2593deb212a9dace5721d6ce0ec1ac8f6

Observation fed5ce68-d56f-42ae-a309-902deba26ce9 · outbound

This paper cites Kahneman,Thinking, fast and slow.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Kahneman,Thinking, fast and slow

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source=pdf_text observed=2026-08-03T15:02:51.560896Z digest=sha256:f59bd4d228155a4d8d6ac3803153ab52ebbade9f63b59a159285eb7498566ce4

Observation 953eaf3d-4cd7-4299-ba5f-bfcb269e284f · outbound

This paper cites an unresolved cited work.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Unresolved cited work

Reference 50

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source=pdf_text observed=2026-08-03T15:02:51.613900Z digest=sha256:229d9a0df97d27381a8b758893d5f2c9d9c9988df52a1efcc8dbab4eacb7e56c

Observation a9f5fd20-cb13-4a0b-8c58-3dadc4a874b7 · outbound

This paper cites Nakahara,Geometry, topology and physics.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Nakahara,Geometry, topology and physics

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source=pdf_text observed=2026-08-03T15:02:51.722054Z digest=sha256:ea365c36350e08c5cf9d9209728ce36e60442627c8a8092202f7839510c0134d

Observation be149ce9-c1a2-4a6b-945c-9ce3576216b3 · outbound

This paper cites Amortized inference in probabilistic reasoning,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Amortized inference in probabilistic reasoning,

Reference 52

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source=pdf_text observed=2026-08-03T15:02:51.783909Z digest=sha256:3d2084a6620223fd2c5899474da1251b85acedf730b7ec4447af6b71fff8ede0

Observation ab776e95-654a-4b2d-aea9-c1ed7f89f13e · outbound

This paper cites The magical number seven, plus or minus two: Some limits on our capacity for processing information.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning The magical number seven, plus or minus two: Some limits on our capacity for processing information

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source=pdf_text observed=2026-08-03T15:02:51.915899Z digest=sha256:78eb2268094cf66794cffbaca59f0e4902d772c17863ef90a6f5ed838745857b

Observation ef8c3666-07d8-463b-a09f-650ba0b807b6 · outbound

This paper cites Canonical microcircuits for predictive coding,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Canonical microcircuits for predictive coding,

Reference 54

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source=pdf_text observed=2026-08-03T15:02:52.083468Z digest=sha256:a3bf5ab56cc66c5d608758bc9f45e3f29ec7c2830b430d0dc3aca7d5403dcc04

Observation ef24c3df-0e4c-41f6-a678-9b7a5aae8db0 · outbound

This paper cites The “wake-sleep.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning The “wake-sleep

Reference 55

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source=pdf_text observed=2026-08-03T15:02:52.174189Z digest=sha256:e577f3430e4260d220dfe988441cb747edef8133b3a92b1721a31d5ead2897de

Observation ad9e5013-5455-4940-94a4-b4fd2c817fc4 · outbound

This paper cites an unresolved cited work.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Unresolved cited work

Reference 56

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source=pdf_text observed=2026-08-03T15:02:52.233536Z digest=sha256:4a30a6a08941340af267e204542c98e774360daf052f4970051d3734ec5c1411

Observation 7a4b5f7c-401c-4c7c-bd1c-bf8c312170da · outbound

This paper cites Pearl,Causality.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Pearl,Causality

Reference 57

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source=pdf_text observed=2026-08-03T15:02:52.286416Z digest=sha256:40c8aae87012ca580aef337dcd69ac6f74dcb14356505f979923288a71fdea69

Observation 1b8f829c-cfe7-446f-b02f-046fe4b0e3b5 · outbound

This paper cites Hippocampal place-cell sequences depict future paths to remembered goals,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Hippocampal place-cell sequences depict future paths to remembered goals,

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source=pdf_text observed=2026-08-03T15:02:52.323107Z digest=sha256:fb1caa95cf8a5b9272842e2e78e599e8ef6a1a0bd47ee6bac28273682d48997d

Observation 68bfc725-2bb7-45bb-88e5-b3d824689d90 · outbound

This paper cites The mechanisms for pattern completion and pattern separation in the hippocampus,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning The mechanisms for pattern completion and pattern separation in the hippocampus,

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source=pdf_text observed=2026-08-03T15:02:52.408450Z digest=sha256:314f111004d96d5a8160594820a56cb67bfe35c679a8afdbc9d675c174da1cd4

Observation 9d2fad0c-ec09-44d9-adca-6869f058b10b · outbound

This paper cites The importance of mixed selectivity in complex cognitive tasks,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning The importance of mixed selectivity in complex cognitive tasks,

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source=pdf_text observed=2026-08-03T15:02:52.486470Z digest=sha256:5343cd812e27278d1bc30265b2935913d94e58317e08cc15e4f22cc85faa8bc5

Observation 6b1f2402-aec3-4ceb-9f3a-733f836ab67d · outbound

This paper cites Linking connectivity, dynamics, and computations in low-rank recurrent neural networks,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Linking connectivity, dynamics, and computations in low-rank recurrent neural networks,

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source=pdf_text observed=2026-08-03T15:02:52.564775Z digest=sha256:97c602b179f238cb4b81238d64b8d4a2b5f13ad30c04e9d79d7e4dafa2f43239

Observation d681becc-2c42-4c62-a540-b101286498ab · outbound

This paper cites an unresolved cited work.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Unresolved cited work

Reference 62

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source=pdf_text observed=2026-08-03T15:02:52.673678Z digest=sha256:f6ac85695cb820ae58004c0490a180562087c3af44fca8fa46e8a0cd8533ca50

Observation c311f8c9-9abd-44fa-b4d5-671ddb2e6caa · outbound

This paper cites Building machines that learn and think like people,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Building machines that learn and think like people,

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source=pdf_text observed=2026-08-03T15:02:52.834485Z digest=sha256:050f9e3da0f1930628734cbb0dde1a1d63b2efa1ec1a41ac55ebc8eb6a883365

Observation 43bf53f5-fea6-41f5-8e7e-0c853ad95230 · outbound

This paper cites How does the brain solve visual object recognition?.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning How does the brain solve visual object recognition?

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source=pdf_text observed=2026-08-03T15:02:52.946134Z digest=sha256:cbf35f238ce8635091b3dc361eb67772f58f708de245f47cd191097517404df2

Observation ccdbd48d-da8b-43cd-959d-839996904ee1 · outbound

This paper cites Predictive reward signal of dopamine neurons,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Predictive reward signal of dopamine neurons,

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source=pdf_text observed=2026-08-03T15:02:53.054471Z digest=sha256:98ee1cc1e96832359a82a9e82e1fbe05d914e44cab44176e25bd53b09f626789

Observation 9b5a5b4e-66a1-4ee8-829f-62a0dbaf4513 · outbound

This paper cites Prefrontal phase locking to hippocampal theta oscillations,.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Prefrontal phase locking to hippocampal theta oscillations,

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source=pdf_text observed=2026-08-03T15:02:53.168467Z digest=sha256:ef10a408eb127556eba9ff65a40f1ea7ae9b96d9bbc69c5a3a76a879da9e256e

Observation c05e28be-7775-4cf7-9ebe-279136ea2658 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Sparks of Artificial General Intelligence: Early experiments with GPT-4

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source=pdf_text observed=2026-08-03T15:02:53.301077Z digest=sha256:7e0e0f7d812abe014e91ef6cf02c34eb68d30c6c6d09755caaee52fc9cf39581

Observation 59798aff-ba17-46d0-a175-d149326a1a96 · outbound

This paper cites an unresolved cited work.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Unresolved cited work

Reference 68

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source=pdf_text observed=2026-08-03T15:02:53.432158Z digest=sha256:e2774c306ae690aee964a28f69cdc6a2e594c2929ff02721331336c8fd1fbb49

Observation c37b68f1-867b-4827-b039-3a07093fa1b2 · outbound

This paper cites an unresolved cited work.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Unresolved cited work

Reference 69

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source=pdf_text observed=2026-08-03T15:02:53.537887Z digest=sha256:44d1d7f887e41a9cfef964c591d215b3a93fc3a088138dabc485c9e057129f92

Observation 06bb7b55-df65-48aa-b420-66e95cbff7e0 · outbound

This paper cites an unresolved cited work.

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning Unresolved cited work

Reference 70

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source=pdf_text observed=2026-08-03T15:02:53.641160Z digest=sha256:161ffb3d141f214fd098b3b48e3a837fb899d5905d8922697b92a1df8e33e8a9

Pith citing papers

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