Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:20:54.014925Z
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 35 inbound Pith citation observations for arXiv:2505.13416.
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 2026-08-15T20:20:54.014925Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T01:10:04.453731Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
46 of 46 outbound references displayed
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Observation 4707b3f0-32f8-4aed-897b-ae4aad481f83 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) The geometry of Sign Gradient Descent,
Reference 1
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Observation 5a4bcb9c-345c-4bb6-9d4e-f3ba9451baab · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Modular Duality in Deep Learning
Reference 2
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Observation 1bee42f3-5f2c-42be-8ceb-bfbc8aa8ba01 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Old Optimizer, New Norm: An Anthology
Reference 3
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Observation 14743439-632c-4e22-a7ed-6f21242cde90 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) On biased compression for distributed learning.Journal of Machine Learning Research, 24(276):1–50, 2023
Reference 4
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Observation 6d3ef052-5b6a-48fa-9530-6fd34870c313 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Robustness to Unbounded Smoothness of Generalized SignSGD
Reference 5
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Observation 9665c334-6091-4e73-a0b3-ac3964307b14 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) A guide through the zoo of biased sgd.Advances in Neural Information Processing Systems, 36:23158–23171, 2023
Reference 6
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Observation edfac4c6-5781-45f8-9167-e1917eca5106 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) An algorithm for quadratic programming.Naval Research Logistics Quarterly, 3(1-2):95–110, 1956
Reference 7
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Observation 476b967b-6f54-47eb-8660-40dbec168ee3 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) The Ball-Proximal (="Broximal") Point Method: a New Algorithm, Convergence Theory, and Applications
Reference 8
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Observation a04c43da-4036-4b89-9930-a617cc82c332 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Parameter-Agnostic Optimization under Relaxed Smoothness
Reference 9
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Observation e611ea2f-29fe-47ad-b9d0-adefc193e91b · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Cifar-10 airbench
Reference 10
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Observation 4f7b456e-c47b-4545-ae66-960b44e28a40 · outbound
Reference 11
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Observation d2f46db5-b347-477f-9ed4-5ec23ae23b1a · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Muon: An optimizer for hidden layers in neural networks, 2024
Reference 12
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Observation 0de49b35-0e29-4558-8ca8-5eb9baf3a853 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-\L{}ojasiewicz Condition
Reference 13
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Observation 60295b72-ddc6-442c-aca9-7dd91f6d4516 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Better Theory for SGD in the Nonconvex World
Reference 14
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Observation 7271be97-0fd7-4add-a491-8bd6076e367c · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Adam: A Method for Stochastic Optimization
Reference 15
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Observation 71fcfa0c-e72a-4410-af0d-4f238ce0ef33 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Understanding Gradient Orthogonalization for Deep Learning via Non-Euclidean Trust-Region Optimization
Reference 16
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Observation 3a4aaccc-5807-4c80-94f3-49dd9d9bb290 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Scalable Optimization in the Modular Norm
Reference 17
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Observation 0194fa99-d066-4862-a18e-6e15e2fe9e8e · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) A Note on the Convergence of Muon
Reference 18
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Observation 417ac115-75f1-449b-a8bc-a512b427781e · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Loss landscapes and optimization in over- parameterized non-linear systems and neural networks.Applied and Computational Harmonic Analysis, 59, 01 2022
Reference 19
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Observation 028cb0e8-4c3a-454e-949c-4db792c06f44 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Muon is Scalable for LLM Training
Reference 20
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Observation 4a704b8d-4120-4225-b90e-d4ab74f0ce2c · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) AdaGrad under Anisotropic Smoothness
Reference 21
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Observation 1986e2e7-1855-4a1e-a9ac-933fd39e6b6e · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Decoupled Weight Decay Regularization
Reference 22
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Observation 79e580b7-1342-4ea4-88ae-b72c088cc8ba · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Scion.https://github.com/LIONS-EPFL/scion.git, 2025
Reference 23
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Observation 8eaa1c86-4cd9-4684-a2c5-8570efffc9d5 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Training Deep Learning Models with Norm-Constrained LMOs
Reference 24
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Observation 9b1c9f91-c0db-4666-a422-a460af5537f0 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) The Frank-Wolfe algorithm: a short introduction
Reference 25
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Observation f4e03318-57b4-4045-8c1d-13f916774b47 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Practical Efficiency of Muon for Pretraining
Reference 26
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Observation eadd520a-8796-426f-a0f6-4d72d9e82931 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Optimizing $(L_0, L_1)$-Smooth Functions by Gradient Methods
Reference 27
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Observation 462ef365-e9fa-4221-b5f4-b897387eb338 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) The Marginal Value of Adaptive Gradient Methods in Machine Learning
Reference 28
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Observation 1aca7122-1d31-47d5-a1bb-5ed1595389c6 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Block- normalized gradient method: An empirical study for training deep neural network, 2018
Reference 29
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Observation d04c7c55-161c-4324-baa4-ebbc8a39c3a6 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Why gradient clipping accelerates training: A theoretical justification for adaptivity
Reference 30
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Observation 9aaed78a-351b-4854-820b-9f53c70b7b0f · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) • Training CNNs
Reference 35
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Observation c1198eb7-63c9-494b-be68-979e8e6de5f3 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Unresolved cited work
Reference 36
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Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Remark 4.Let us compare bounds(17) and (19)
Reference 37
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Observation 1198f803-0260-4ae9-abf8-a6715695df40 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Unresolved cited work
Reference 38
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Observation ce2fc8f7-30e2-4818-b02b-4f4432400c93 · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Since the functionψ is increasing fort >0, ψ−1 exists
Reference 39
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Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Unresolved cited work
Reference 40
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Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Unresolved cited work
Reference 41
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Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Unresolved cited work
Reference 42
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Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) −tk i∥∇ifξk(Xk)∥(i)⋆ +tk i∥∇if(Xk)−∇ifξk(Xk)∥(i)⋆ + L0 i +L1 i∥∇if(Xk)∥(i)⋆ 2 tk i 2 # ≤f(Xk) + pX i=1
Reference 43
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Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Unresolved cited work
Reference 44
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Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Since the functionψ is increasing fort> 0, ψ−1 exists
Reference 45
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Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Unresolved cited work
Reference 46
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Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) D ∇if(Xk),Xk+1 i −Xk i E (i) + L0 i +L1 i∥∇if(Xk)∥(i)⋆ 2 ∥Xk i −Xk+1 i ∥2 (i) # = f(Xk) + pX i=1
Reference 47
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Observation 707beac3-ca49-4756-8f35-369b2ef9cdaa · outbound
Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) The Geometry of Sign Gradient Descent
Reference 2020
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Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization
Reference 2021
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Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs) Unresolved cited work
Reference 2024
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SGD with Adaptive Preconditioning: Unified Analysis and Momentum Acceleration Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 44
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Simple Stepsize for Quasi-Newton Methods with Global Convergence Guarantees Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 1697
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Low-rank Orthogonalization for Large-scale Matrix Optimization with Applications to Foundation Model Training Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 43
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DeMuon: A Decentralized Muon for Matrix Optimization over Graphs Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
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Why Do We Need Warm-up? A Theoretical Perspective Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 52
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Preconditioned Norms: A Unified Framework for Steepest Descent, Quasi-Newton and Adaptive Methods Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 15
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Non-Euclidean SGD for Structured Optimization: Unified Analysis and Improved Rates Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 46
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Turbo-Muon: Almost-Orthogonal Pre-Conditioning for Fast Muon Updates Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 30
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Hierarchical Semantic Correlation-Aware Masked Autoencoder for Unsupervised Audio-Visual Representation Learning Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 22
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Communication-Efficient Gluon in Federated Learning Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 32
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Reference 20
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Muon with Nesterov Momentum: Heavy-Tailed Noise and (Randomized) Inexact Polar Decomposition Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 43
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Local LMO: Constrained Gradient Optimization via a Local Linear Minimization Oracle Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 27
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Observation 735db6c0-d70e-4e20-84e1-27ad06c33f70 · inbound
Intrinsic Muon: Spectral Optimization on Riemannian Matrix Manifolds Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 51
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Observation 31fe0f84-231d-4823-bbf3-461b53326504 · inbound
Phases of Muon: When Muon Eclipses SignSGD Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 63
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Observation a2a3fb1b-d128-45ec-9d7d-2ece8cb301c5 · inbound
Constrained Stochastic Spectral Preconditioning Converges for Nonconvex Objectives Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 56
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Observation f9874835-7e65-4b90-ad62-dd2862a588f9 · inbound
Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 59
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Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 132
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Observation efbc976d-7e8e-47e0-b8e1-62996c62c824 · inbound
Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 134
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Observation 4de886da-5418-4f81-b0af-1259e899adb4 · inbound
Ringmaster LMO: Asynchronous Linear Minimization Oracle Momentum Method Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 299
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Observation 66c05d6b-7ffb-47a8-9121-8ac607731255 · inbound
MiMuon: Mixed Muon Optimizer with Improved Generalization for Large Models Gluon: Making Muon & Scion Great Again! (Bridging Theory and Practice of LMO-based Optimizers for LLMs)
Reference 31
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Reference 300
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Reference 32
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Reference 19
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Reference 64
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Reference 23
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Reference 14
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