Paper Citation Record · LEDGER

Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2411.18704.

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

pith.paper-citation-record.v1
2411.18704 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 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 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:09:13.181478Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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External citation measurements

18
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b810eb72-d2f1-430a-9712-fe4029009027 · inbound

DMAF-Net: An Effective Modality Rebalancing Framework for Incomplete Multi-Modal Medical Image Segmentation cites this paper.

DMAF-Net: An Effective Modality Rebalancing Framework for Incomplete Multi-Modal Medical Image Segmentation Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:13.181478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6317d71f-22a8-4dbf-8bef-da88f1698b5f · inbound

Demonstration of Efficient Predictive Surrogates for Large-scale Quantum Processors cites this paper.

Demonstration of Efficient Predictive Surrogates for Large-scale Quantum Processors Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 158

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:19.021070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8450b01c-318c-4aff-b0e4-336fa8787dcb · inbound

A Generalisable Generative Model for Multi-Detector Calorimeter Simulation cites this paper.

A Generalisable Generative Model for Multi-Detector Calorimeter Simulation Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-04T21:53:53.411252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 399ad1e9-61e3-4ace-9e02-9eb07475a168 · inbound

LayerPipe2: Multistage Pipelining and Weight Recompute via Improved Exponential Moving Average for Training Neural Networks cites this paper.

LayerPipe2: Multistage Pipelining and Weight Recompute via Improved Exponential Moving Average for Training Neural Networks Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-17T00:38:44.801439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6b7bd5e7-e8b3-4811-81c8-dc21a8de5f9f · inbound

Vibrational infrared and Raman spectra of the methanol molecule with equivariant neural-network property surfaces cites this paper.

Vibrational infrared and Raman spectra of the methanol molecule with equivariant neural-network property surfaces Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 103

Resolution: verified exact; arxiv_id, observed 2026-05-15T21:06:37.977236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3ca9d6d7-9d16-46b3-b60b-a32eedb0855b · inbound

MC-GenRef: Annotation-free mammography microcalcification segmentation with generative posterior refinement cites this paper.

MC-GenRef: Annotation-free mammography microcalcification segmentation with generative posterior refinement Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:20:47.518454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 14c74eb3-f1ea-4cc8-90e2-2895e3ce8cc0 · inbound

\mathsf{VISTA}: Decentralized Machine Learning in Adversary Dominated Environments cites this paper.

\mathsf{VISTA}: Decentralized Machine Learning in Adversary Dominated Environments Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-11T02:30:55.180775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8361b2ff-0a22-43ed-ad84-678d1d21dc66 · inbound

Spatial Adapter: Structured Spatial Decomposition and Closed-Form Covariance for Frozen Predictors cites this paper.

Spatial Adapter: Structured Spatial Decomposition and Closed-Form Covariance for Frozen Predictors Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T01:42:03.935250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8fd50e4e-6fe6-4dea-811f-f3d2940e81ec · inbound

A Unified Graph Language Model for Multi-Domain Multi-Task Graph Alignment Instruction Tuning cites this paper.

A Unified Graph Language Model for Multi-Domain Multi-Task Graph Alignment Instruction Tuning Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:42:26.020429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b406aa8e-8598-498d-8a92-b7e31a8afa00 · inbound

Generation of Heterogeneous PET Images from Uniform Organ Activity Maps Using a Pretrained Domain-Adapted Diffusion Model cites this paper.

Generation of Heterogeneous PET Images from Uniform Organ Activity Maps Using a Pretrained Domain-Adapted Diffusion Model Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:34:02.473009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation beb105b7-3319-4705-9e3f-8047217b6ffd · inbound

Refined Analysis of Entropy-Regularized Actor-Critic cites this paper.

Refined Analysis of Entropy-Regularized Actor-Critic Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:14:47.327093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 26fc57a2-5e3d-4f08-8f1d-ea34cf53988f · inbound

Stabilizing distribution-free probabilistic forecasts cites this paper.

Stabilizing distribution-free probabilistic forecasts Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T14:03:29.142417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ae1f20ff-fce4-4c6b-9adb-6ddb1c058e79 · inbound

EMAgnet: Parameter-Space EMA Regularization for Policy Gradient Self-Play in Large Games cites this paper.

EMAgnet: Parameter-Space EMA Regularization for Policy Gradient Self-Play in Large Games Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:49:45.639309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 870ed7e4-a4ac-4b81-b768-74d500a60641 · inbound

No Adaptation Without Observation: Observability-Constrained Test-Time Prompt Tuning for LiDAR Semantic Segmentation cites this paper.

No Adaptation Without Observation: Observability-Constrained Test-Time Prompt Tuning for LiDAR Semantic Segmentation Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-01T12:55:43.911937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4a672f2d-432e-4b9f-9a49-4e267fc17f6c · inbound

Exploring Line Bundle Standard Models with Transformers cites this paper.

Exploring Line Bundle Standard Models with Transformers Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-07-02T18:37:15.916652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 31a0a251-0e4a-4cce-ae30-0a13e4857d92 · inbound

Exploring Line Bundle Standard Models with Transformers cites this paper.

Exploring Line Bundle Standard Models with Transformers Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-02T09:22:54.422511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82d1d3ed-db9e-4323-ad4e-915e815aa877 · inbound

Optimizing Visual Generative Models via Distribution-wise Rewards cites this paper.

Optimizing Visual Generative Models via Distribution-wise Rewards Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-03T16:48:39.762036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 531a8535-f988-414d-811c-2cedb2f5c5f9 · inbound

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games cites this paper.

FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 11

Resolution: metadata mismatch; local_arxiv, observed 2026-07-08T03:24:28.858597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 57779104-0edf-4b6d-beba-f3fb20d5e6a1 · inbound

Beyond Token-Level Cross-Entropy: Fr\'echet Distributional Post-Training for Autoregressive Image Generation cites this paper.

Beyond Token-Level Cross-Entropy: Fr\'echet Distributional Post-Training for Autoregressive Image Generation Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T00:44:16.863007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.