Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:29:46.598779Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 78 of 78 outbound references and 2 inbound Pith citation observations for arXiv:2506.05259.
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 2026-08-07T10:29:46.598779Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:59:58.728215Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T09:34:46.796448Z
78 of 78 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 281017e3-dabd-4764-9d1e-201deee15183 · outbound
Learning long range dependencies through time reversal symmetry breaking Resurrecting recurrent neural networks for long sequences
Reference 1
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Observation 4fe2e771-77e7-471f-82d7-93ef7277e1a7 · outbound
Learning long range dependencies through time reversal symmetry breaking Combining recurrent, convolutional, and continuous-time models with linear state space layers
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 77222ca7-a725-41f9-963d-a4c7a120755c · outbound
Learning long range dependencies through time reversal symmetry breaking Efficiently Modeling Long Sequences with Structured State Spaces
Reference 3
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Observation c5f9d62e-e734-43f0-9e65-65761888c7d6 · outbound
Learning long range dependencies through time reversal symmetry breaking Diagonal state spaces are as effective as structured state spaces
Reference 4
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Observation ca711b2b-9a94-42e7-bf9b-834dc54f1ba9 · outbound
Learning long range dependencies through time reversal symmetry breaking Simplified State Space Layers for Sequence Modeling
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 375b8519-85d7-4019-8d89-67609bff4387 · outbound
Learning long range dependencies through time reversal symmetry breaking Mamba: Linear-Time Sequence Modeling with Selective State Spaces
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Observation 2c5b9417-15a3-490d-9b3e-11773de8c831 · outbound
Learning long range dependencies through time reversal symmetry breaking The hardware lottery
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Observation 305936de-fd35-4fdc-9280-c3a4c957c0c9 · outbound
Learning long range dependencies through time reversal symmetry breaking Attention is all you need
Reference 8
Source-reported events for the cited work
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Observation ab12caa5-7c72-45b8-a0cc-e3f2656e5684 · outbound
Learning long range dependencies through time reversal symmetry breaking The hardware is the software
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Observation 3e64e34f-0179-4997-88d2-f276d2ceea55 · outbound
Learning long range dependencies through time reversal symmetry breaking Self-learning machines based on hamiltonian echo backpropagation
Reference 10
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Observation 6f210341-9002-468e-867e-b4f4be73a5e9 · outbound
Learning long range dependencies through time reversal symmetry breaking Training of Physical Neural Networks
Reference 11
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Observation 29d065fb-c8a9-47ba-8010-71d67d6711be · outbound
Learning long range dependencies through time reversal symmetry breaking Automatic differentiation in machine learning: a survey
Reference 12
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Unavailable: canonical work link unavailable.
Observation 2a227184-a792-47e0-91b8-17254905c8f5 · outbound
Learning long range dependencies through time reversal symmetry breaking A learning algorithm for continually running fully recurrent neural networks
Reference 13
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Observation c79d7f24-1a6a-4fd4-88a9-9045672be392 · outbound
Learning long range dependencies through time reversal symmetry breaking Online learning of long-range dependencies
Reference 14
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Observation 3233fcfa-c10b-43a5-9d71-ed0d74499c31 · outbound
Learning long range dependencies through time reversal symmetry breaking Unbiased Online Recurrent Optimization
Reference 15
Source-reported events for the cited work
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Observation e4b0d576-1c58-4bfb-98ab-13a09bd9c4d7 · outbound
Learning long range dependencies through time reversal symmetry breaking A solution to the learning dilemma for recurrent networks of spiking neurons
Reference 16
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Observation aecb07af-5b3d-418e-b5f9-6ff14d2e7e82 · outbound
Learning long range dependencies through time reversal symmetry breaking A Truly Sparse and General Implementation of Gradient-Based Synaptic Plasticity
Reference 17
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Observation 048b5a2c-3ef8-4569-b034-65878233ad6f · outbound
Learning long range dependencies through time reversal symmetry breaking Accelerating stochastic gradient descent using predictive variance reduction
Reference 18
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Observation dfb8ff2f-0fb7-438e-b644-381b727db9d2 · outbound
Learning long range dependencies through time reversal symmetry breaking Stochastic Subspace Descent
Reference 19
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Observation af2c1023-f5cb-4751-a34d-5f5f6037e13a · outbound
Learning long range dependencies through time reversal symmetry breaking Multivariate stochastic approximation using a simultaneous perturbation gradient approximation
Reference 20
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Observation 8f07c399-256d-4e03-9f07-bf007d380599 · outbound
Learning long range dependencies through time reversal symmetry breaking Model of birdsong learning based on gradient estimation by dynamic perturbation of neural conductances
Reference 21
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Observation a7db0ae1-bb54-43e8-9980-2cfe86bcbe96 · outbound
Learning long range dependencies through time reversal symmetry breaking Scaling Forward Gradient With Local Losses
Reference 22
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Unavailable: canonical work link unavailable.
Observation f4503e48-6ecd-4e1b-b4aa-0a3780f6d05e · outbound
Learning long range dependencies through time reversal symmetry breaking Learning by directional gradient descent
Reference 23
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Observation b4c84264-0dbf-4095-8e30-e9b4393c0515 · outbound
Learning long range dependencies through time reversal symmetry breaking Can forward gradient match backpropagation? In International Conference on Machine Learning, pages 10249–10264
Reference 24
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Observation c48a6307-d456-4c77-9238-99007baa7320 · outbound
Learning long range dependencies through time reversal symmetry breaking Fine-tuning language models with just forward passes
Reference 25
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Observation 9eca4ab4-110c-47c1-a2bd-f301f4ad1e45 · outbound
Learning long range dependencies through time reversal symmetry breaking A cookbook for hardware-friendly implicit learning on static data
Reference 26
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Observation 6cba4313-f33e-4cf9-bf95-d7867a643109 · outbound
Learning long range dependencies through time reversal symmetry breaking Equilibrium propagation: Bridging the gap between energy-based models and backpropagation
Reference 27
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Observation b04d74f9-292d-48c4-b345-830fb5531cb0 · outbound
Learning long range dependencies through time reversal symmetry breaking Mathematical theory of optimal processes
Reference 28
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Observation 26e7acba-4e17-4ebe-9966-ea6863428590 · outbound
Learning long range dependencies through time reversal symmetry breaking Oscillatory State-Space Models
Reference 29
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Observation 8a59e09c-57e0-4faf-be0d-1bb54f72f5ab · outbound
Learning long range dependencies through time reversal symmetry breaking Unicornn: A recurrent model for learning very long time dependencies
Reference 30
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Observation d626989b-5aa5-4faf-87ce-b2eb80003a8c · outbound
Learning long range dependencies through time reversal symmetry breaking Neural ordinary differential equations
Reference 31
Source-reported events for the cited work
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Observation b51d4256-1ee7-40d6-8339-a5bd482a0644 · outbound
Learning long range dependencies through time reversal symmetry breaking The Elements of Differentiable Programming
Reference 32
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Observation 822c1b56-b813-4841-8969-fac028c9be71 · outbound
Learning long range dependencies through time reversal symmetry breaking Numerical methods for ordinary differential equations
Reference 33
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Observation 9eea6805-7850-4c88-8220-a3237ee893e0 · outbound
Learning long range dependencies through time reversal symmetry breaking Log neural controlled differential equations: The lie brackets make a difference
Reference 34
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Observation 829825ed-2a28-4011-82a7-1250efbe0952 · outbound
Learning long range dependencies through time reversal symmetry breaking The UEA multivariate time series classification archive, 2018
Reference 35
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Observation 9c115af8-623e-43c2-accf-df8200eddda5 · outbound
Learning long range dependencies through time reversal symmetry breaking Deep ppg: Large-scale heart rate estimation with convolutional neural networks
Reference 36
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Observation ce341d79-4494-4c35-8141-e5422b535a07 · outbound
Learning long range dependencies through time reversal symmetry breaking Scaling equilibrium propagation to deep convnets by drastically reducing its gradient estimator bias
Reference 37
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Observation 8b740734-ad56-408a-a945-5585411066b5 · outbound
Learning long range dependencies through time reversal symmetry breaking Symplectic Recurrent Neural Networks
Reference 38
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Observation 87bb92c4-1814-41d6-9bc9-a04042e6453e · outbound
Learning long range dependencies through time reversal symmetry breaking Hamiltonian neural networks.Advances in neural information processing systems, 32, 2019
Reference 39
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Observation 246a17f6-32de-436f-bd24-25774f7a07d9 · outbound
Learning long range dependencies through time reversal symmetry breaking Lagrangian Neural Networks
Reference 40
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Observation 4b987e41-7265-481e-bf90-4022177d76e8 · outbound
Learning long range dependencies through time reversal symmetry breaking Hamiltonian Generative Networks
Reference 41
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Observation 7fc416e9-53a5-4c0b-9637-6451a319a608 · outbound
Learning long range dependencies through time reversal symmetry breaking Hybrid monte carlo
Reference 42
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Observation a1a24142-14a6-45e2-8852-f290c459249b · outbound
Learning long range dependencies through time reversal symmetry breaking Mcmc using hamiltonian dynamics
Reference 43
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Observation 8ae4701e-9f1d-44f1-b13a-45fae1d4e852 · outbound
Learning long range dependencies through time reversal symmetry breaking Magnetic hamiltonian monte carlo
Reference 44
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Observation d85bf66d-0a09-4479-8e73-216c9c9f545d · outbound
Learning long range dependencies through time reversal symmetry breaking Memory-Efficient Optimization with Factorized Hamiltonian Descent
Reference 45
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Observation d804dd90-62f2-4172-9334-cf94bde76e5f · outbound
Learning long range dependencies through time reversal symmetry breaking Supervised learning in physical networks: From machine learning to learning machines
Reference 46
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Learning long range dependencies through time reversal symmetry breaking Holomorphic equilibrium propagation computes exact gradients through finite size oscillations
Reference 47
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Observation 992e0393-bc65-4d1c-879a-65e1e12a9527 · outbound
Learning long range dependencies through time reversal symmetry breaking Energy-based learning algorithms for analog computing: a comparative study
Reference 48
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Observation 21704beb-ebea-4c2b-8d93-a2d00a2c60be · outbound
Learning long range dependencies through time reversal symmetry breaking Towards training digitally-tied analog blocks via hybrid gradient computation
Reference 49
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Observation 22384ae5-1439-4722-8685-3c9f5b33aab2 · outbound
Learning long range dependencies through time reversal symmetry breaking A Fast Algorithm to Simulate Nonlinear Resistive Networks
Reference 50
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Observation 486773ce-89b3-42e0-86be-8f2b708b168e · outbound
Learning long range dependencies through time reversal symmetry breaking Agnostic Physics-Driven Deep Learning
Reference 51
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Observation c359c44c-06d6-4d87-8969-fc6da2d8cf86 · outbound
Learning long range dependencies through time reversal symmetry breaking Abreu, I
Reference 52
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Observation cf09e175-9dd8-409c-aca6-87e6ea83f8c4 · outbound
Learning long range dependencies through time reversal symmetry breaking SuperMind: A survey of the potential of superconducting electronics for neuromorphic computing
Reference 53
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Observation 9e9f331f-a1c3-447b-b5ae-55a32e26e5af · outbound
Learning long range dependencies through time reversal symmetry breaking Grollier, D
Reference 54
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Observation a3e3936e-5030-4dba-b3f8-0244601629d6 · outbound
Learning long range dependencies through time reversal symmetry breaking Gaussian Error Linear Units (GELUs), June 2023
Reference 55
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Observation 064d975d-fdc7-455d-9d8f-86cfc2a51194 · outbound
Learning long range dependencies through time reversal symmetry breaking Dauphin, Angela Fan, Michael Auli, and David Grangier
Reference 56
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Observation 4f3e9b97-45d8-4056-8cff-46661d4e6caf · outbound
Learning long range dependencies through time reversal symmetry breaking JAX: composable transformations of Python+NumPy programs, 2018
Reference 57
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Learning long range dependencies through time reversal symmetry breaking Unresolved cited work
Reference 59
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Learning long range dependencies through time reversal symmetry breaking Unresolved cited work
Reference 60
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Learning long range dependencies through time reversal symmetry breaking Unresolved cited work
Reference 61
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Learning long range dependencies through time reversal symmetry breaking Unresolved cited work
Reference 62
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Observation 6b1a9a77-e3e0-448b-8720-fe312f563e28 · outbound
Learning long range dependencies through time reversal symmetry breaking Unresolved cited work
Reference 63
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Learning long range dependencies through time reversal symmetry breaking Remark 1
Reference 64
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Reference 65
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Learning long range dependencies through time reversal symmetry breaking Unresolved cited work
Reference 66
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Reference 67
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Learning long range dependencies through time reversal symmetry breaking Unresolved cited work
Reference 68
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Learning long range dependencies through time reversal symmetry breaking Note that while we did not assume in the main part of this manuscript that ℓ depended on θ, we assume it in the appendix for the generality of our derivations
Reference 69
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Learning long range dependencies through time reversal symmetry breaking Unresolved cited work
Reference 70
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Learning long range dependencies through time reversal symmetry breaking Unresolved cited work
Reference 71
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Learning long range dependencies through time reversal symmetry breaking Proof of Lemma A.1
Reference 72
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Learning long range dependencies through time reversal symmetry breaking V and T only depend on ϕ and π respectively: V [Φ, θ, u] = V [ϕ, θ, u], T [Φ, θ, u] = T [π, θ, u]
Reference 73
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Learning long range dependencies through time reversal symmetry breaking Unresolved cited work
Reference 74
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Learning long range dependencies through time reversal symmetry breaking Remark 4
Reference 75
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Learning long range dependencies through time reversal symmetry breaking Unresolved cited work
Reference 76
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Learning long range dependencies through time reversal symmetry breaking chain rule
Reference 77
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Observation 473b6529-c0e0-4fed-a184-d236db1bd56d · outbound
Learning long range dependencies through time reversal symmetry breaking I − δ2 2 A δ[I − δ2 4 A] −δA I − δ2 2 A # , F k =
Reference 78
Source-reported events for the cited work
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Learning long range dependencies through time reversal symmetry breaking doi: 10.1016/j.revip.2024.100093
Reference 2024
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Equilibrium Propagation for Dissipative Dynamics Learning long range dependencies through time reversal symmetry breaking
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Equilibrium Propagation and Hamiltonian Inference in the Diffusive Fitzhugh-Nagumo Model Learning long range dependencies through time reversal symmetry breaking
Reference 28
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