Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T19:03:06.128110Z
Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 1 inbound Pith citation observation for arXiv:2412.07224.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T19:03:06.128110Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-13T06:26:20.393476Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T06:27:24.508641Z
84 of 84 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation d9949f2d-90b6-46b8-8e7a-bc8eda0a52bc · outbound
Parseval Regularization for Continual Reinforcement Learning Loss of Plasticity in Continual Deep Reinforcement Learning
Reference 1
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Unavailable: canonical work link unavailable.
Observation 4e483e6a-841b-4f7e-880c-4b057be21308 · outbound
Parseval Regularization for Continual Reinforcement Learning Critical Learning Periods in Deep Neural Networks
Reference 2
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Observation bea16c5f-c88a-4bbb-a24a-712c776ebd3c · outbound
Parseval Regularization for Continual Reinforcement Learning Agarwal, M
Reference 3
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Observation c2bbcaa0-be32-4c95-b880-c377da0f3480 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 4
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Observation 4f15c555-aed4-42c6-8c86-792e70b39711 · outbound
Parseval Regularization for Continual Reinforcement Learning Ash and R
Reference 5
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Observation 8545cf11-27f7-44ae-b9fc-c54edd547a5e · outbound
Parseval Regularization for Continual Reinforcement Learning Layer Normalization
Reference 6
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Observation 9504f469-2e2e-449f-936e-754550c1c3c0 · outbound
Parseval Regularization for Continual Reinforcement Learning Bachlechner, B
Reference 7
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Observation 2c222379-ada4-4493-b81f-d502ee3b75f9 · outbound
Parseval Regularization for Continual Reinforcement Learning Balduzzi, M
Reference 8
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Observation aa7c5c56-21c7-4826-8abe-814ee965d67f · outbound
Parseval Regularization for Continual Reinforcement Learning CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning
Reference 9
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Observation 4e74fbb8-8c35-4abf-bf9f-378ea74a994f · outbound
Parseval Regularization for Continual Reinforcement Learning Blumenfeld, D
Reference 10
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Observation 34d038d0-2759-438a-9097-4ce4f49451a2 · outbound
Parseval Regularization for Continual Reinforcement Learning Cisse, P
Reference 11
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Observation 4071d506-5b6b-4840-a554-bb28b80e121d · outbound
Parseval Regularization for Continual Reinforcement Learning Continual Backprop: Stochastic Gradient Descent with Persistent Randomness
Reference 12
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Observation 0ea83032-b837-4024-8ad4-9ec3ed2ad9df · outbound
Parseval Regularization for Continual Reinforcement Learning D’Oro, M
Reference 13
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Observation 0fb1a9f2-8205-4ebc-815d-57f8d9d76f1b · outbound
Parseval Regularization for Continual Reinforcement Learning Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning
Reference 14
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Observation f824c724-2a32-4e0c-88e3-d5761e0f9c1d · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 15
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Observation ffbe944b-2c95-43c9-815c-7bc77200aeb5 · outbound
Parseval Regularization for Continual Reinforcement Learning Glorot and Y
Reference 16
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Observation 9418ad2f-8394-452b-81d0-b100ac08a5bf · outbound
Parseval Regularization for Continual Reinforcement Learning An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
Reference 17
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Observation ba482d8d-087c-4a0d-b213-ee52e8ddfa86 · outbound
Parseval Regularization for Continual Reinforcement Learning Gulrajani, F
Reference 18
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Observation c0596d99-a4ae-47f2-881b-f25bc20f3740 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 19
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Observation f1ada359-5b73-42fd-9d0d-b856a43698b3 · outbound
Parseval Regularization for Continual Reinforcement Learning Hanin and D
Reference 20
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Observation 34b26e73-7bc7-4519-b214-85c80cc98a02 · outbound
Parseval Regularization for Continual Reinforcement Learning TD-MPC2: Scalable, Robust World Models for Continuous Control
Reference 21
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Observation 8e290d92-5d85-47f2-adba-4d1a1b7d1071 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 22
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Observation 2c581440-faca-4d51-905f-2bb20b467ba9 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 23
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Observation 90c77222-1aff-4fa0-adbb-b9977c00e142 · outbound
Parseval Regularization for Continual Reinforcement Learning Gaussian Error Linear Units (GELUs)
Reference 24
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Observation c8421c13-5e70-4800-a88a-caedb775cce5 · outbound
Parseval Regularization for Continual Reinforcement Learning Hochreiter, Y
Reference 25
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Observation c4dc4454-b080-48c2-841b-862391a3a133 · outbound
Parseval Regularization for Continual Reinforcement Learning Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks
Reference 26
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Observation 157214e9-ca1f-487c-a054-bb2265e829df · outbound
Parseval Regularization for Continual Reinforcement Learning Huang, R
Reference 27
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Observation 1156dfb0-15fe-430a-874a-1bd158842724 · outbound
Parseval Regularization for Continual Reinforcement Learning Huang, R
Reference 28
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Observation 942d7a9f-969b-46dc-91fc-1cf83d5aa1d0 · outbound
Parseval Regularization for Continual Reinforcement Learning Jastrzebski, D
Reference 29
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Observation db7a9c77-d3f1-48aa-a59b-6b4fbd59e397 · outbound
Parseval Regularization for Continual Reinforcement Learning Towards Continual Reinforcement Learning: A Review and Perspectives
Reference 30
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Observation e419908d-5ef0-47f8-ab32-c900acb93a3a · outbound
Parseval Regularization for Continual Reinforcement Learning Kirkpatrick, R
Reference 31
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Observation deaf26a5-fdbf-46ca-8a40-d3075809a641 · outbound
Parseval Regularization for Continual Reinforcement Learning Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
Reference 32
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Observation 533425b0-bec2-48c7-b74e-ad79c2eeaadb · outbound
Parseval Regularization for Continual Reinforcement Learning Maintaining Plasticity in Continual Learning via Regenerative Regularization
Reference 33
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Observation c0b47285-4e44-4430-8b50-00592f1b4561 · outbound
Parseval Regularization for Continual Reinforcement Learning Directions of Curvature as an Explanation for Loss of Plasticity
Reference 34
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Observation 5e86b1dd-f67c-4205-a9b7-f13b96efe150 · outbound
Parseval Regularization for Continual Reinforcement Learning Lopez-Paz and M
Reference 35
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Observation 4d780947-265b-489f-be6e-901188b06b55 · outbound
Parseval Regularization for Continual Reinforcement Learning Decoupled Weight Decay Regularization
Reference 36
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Observation a1a15da9-0dad-46a7-929d-d6a505e969f1 · outbound
Parseval Regularization for Continual Reinforcement Learning Understanding and Preventing Capacity Loss in Reinforcement Learning
Reference 37
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Observation 3b90884f-b7af-43f7-80cb-bc0f3a9c0c8a · outbound
Parseval Regularization for Continual Reinforcement Learning Understanding plasticity in neural networks
Reference 38
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Observation 41119827-6b0f-41c5-96f4-033365c56099 · outbound
Parseval Regularization for Continual Reinforcement Learning Masarczyk, M
Reference 39
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Observation 6e9645b1-bb8b-430c-a0fa-e896b61f0dbe · outbound
Parseval Regularization for Continual Reinforcement Learning Mish: A Self Regularized Non-Monotonic Activation Function
Reference 40
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Observation 54f779a2-d022-4753-8d85-2435310741e5 · outbound
Parseval Regularization for Continual Reinforcement Learning Nair and G
Reference 41
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Observation a4973c65-5ed9-46dd-9577-0b5a43eb0b0c · outbound
Parseval Regularization for Continual Reinforcement Learning Neyshabur, H
Reference 42
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Observation 027c3a97-f546-44af-9815-81a10eb9bdf3 · outbound
Parseval Regularization for Continual Reinforcement Learning Nikishin, M
Reference 43
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Observation f807b444-6cfd-4e13-986d-7a2a7f748f95 · outbound
Parseval Regularization for Continual Reinforcement Learning Deep Reinforcement Learning with Plasticity Injection
Reference 44
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Observation 7e5bb0c1-baee-41dc-99e8-5ee25f8e99a6 · outbound
Parseval Regularization for Continual Reinforcement Learning Papyan, X
Reference 45
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Observation 77e0512b-96e5-4754-9814-1a506dfca13c · outbound
Parseval Regularization for Continual Reinforcement Learning Pascanu, T
Reference 46
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Observation 833b6d3a-b60b-415f-8f22-c48593e9eb9b · outbound
Parseval Regularization for Continual Reinforcement Learning Pennington, S
Reference 47
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Observation e0503123-a277-476f-9c95-3b981569eec1 · outbound
Parseval Regularization for Continual Reinforcement Learning Pennington, S
Reference 48
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Parseval Regularization for Continual Reinforcement Learning Prach and C
Reference 49
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Observation ed56f596-5af4-4a85-a933-8f8d28eab0ab · outbound
Parseval Regularization for Continual Reinforcement Learning Robust Policy Optimization in Deep Reinforcement Learning
Reference 50
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Observation 89743bb9-b1f8-41cd-b90f-7bd4ac826667 · outbound
Parseval Regularization for Continual Reinforcement Learning Searching for Activation Functions
Reference 51
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Observation 5e208645-50d8-4051-96db-0991404e58ec · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 52
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Observation 89094e43-0fd3-4ae8-b177-89bb51940222 · outbound
Parseval Regularization for Continual Reinforcement Learning Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
Reference 53
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Observation 11e46c8a-c6c2-4034-bf52-c83cc3cc7f3d · outbound
Parseval Regularization for Continual Reinforcement Learning Proximal Policy Optimization Algorithms
Reference 54
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Observation 7a457bbd-7313-44ca-957c-53b320ff270a · outbound
Parseval Regularization for Continual Reinforcement Learning Shang, K
Reference 55
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Observation 2be53658-1989-4c2f-a301-c5acf3aae9c4 · outbound
Parseval Regularization for Continual Reinforcement Learning Singla and S
Reference 56
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Observation 8faf7770-c20d-415e-a71e-c995c1baae75 · outbound
Parseval Regularization for Continual Reinforcement Learning The Dormant Neuron Phenomenon in Deep Reinforcement Learning
Reference 57
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Observation db4c823c-0aa4-44d4-b7d8-e7f98bdc68dd · outbound
Parseval Regularization for Continual Reinforcement Learning Human-Timescale Adaptation in an Open-Ended Task Space
Reference 58
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Observation a9afb267-f4c2-4a47-a03a-6bc60de034e2 · outbound
Parseval Regularization for Continual Reinforcement Learning Vaswani, N
Reference 59
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Observation 0091146f-bdd6-4a59-adee-1939ccec6f77 · outbound
Parseval Regularization for Continual Reinforcement Learning Continual Learning: Applications and the Road Forward
Reference 60
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Observation 83f0e510-359f-45f1-a778-a5fa65db140c · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 61
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Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 62
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Observation 9c65e01d-846c-4824-a54a-288e0c8eefa4 · outbound
Parseval Regularization for Continual Reinforcement Learning Zaidi, T
Reference 63
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Parseval Regularization for Continual Reinforcement Learning Fixup Initialization: Residual Learning Without Normalization
Reference 64
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Observation 404cd513-52ea-49e8-8a76-b88973394050 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 65
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Observation 2732916d-dcb1-422a-8635-6f62898dc576 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 66
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Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 67
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Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
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Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 69
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Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 70
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Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 71
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Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
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Observation a5a602af-7c61-4e2d-ae00-694b6c2853e4 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 73
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Observation f44aa096-bad0-41d8-80f7-d22fd2ffe540 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 74
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Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
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Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
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Observation 1903416f-1bcf-485a-be13-4b690478649b · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
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Observation 60be6286-6303-4efc-a7b8-7f7309bf0407 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 78
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Observation c1183c44-accd-4404-a124-be0697fac14b · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
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Observation 2b19e059-ace4-4058-8783-d59d1dbbed9f · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 80
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Observation f6fe8a65-ed24-4c83-a09f-52aa2528c9c4 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 81
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Observation 2e7dd68b-82b2-48ee-b48a-4e9564875eb6 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 82
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Observation 760d268b-353c-41a7-97cf-f21bf2bda5d0 · outbound
Parseval Regularization for Continual Reinforcement Learning Unresolved cited work
Reference 83
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Observation 9a4d3fe9-e78f-4cb3-81d3-74362134b336 · outbound
Parseval Regularization for Continual Reinforcement Learning So due to the seed, the same environment (e.g
Reference 84
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Observation 9a50ba15-a2d9-42f1-b26d-0098c1bb149e · inbound
Rotation-Preserving Supervised Fine-Tuning Parseval Regularization for Continual Reinforcement Learning
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