LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization | Paper Citation Record

Observation c3df81d5-a9b9-4f62-8b19-f1a8d59d465a · outbound

This paper cites Towards understanding sharpness-aware minimization.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Towards understanding sharpness-aware minimization

Reference 1

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Observation c57dff82-1239-4736-8dfe-4d8778822dfe · outbound

This paper cites Tensor programs v: Tuning large neural networks via zero-shot hyperparameter transfer.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Tensor programs v: Tuning large neural networks via zero-shot hyperparameter transfer

Reference 2

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Observation 34f9c036-c826-4470-845e-68f2f7ac3762 · outbound

This paper cites A fast iterative shrinkage-thresholding algorithm for linear inverse problems.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization A fast iterative shrinkage-thresholding algorithm for linear inverse problems

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.836229Z

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Observation ea4f51d3-ee42-4ea6-8454-d3ab5cbb1359 · outbound

This paper cites mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:12:35.985578Z

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Observation 99d6613a-b92c-45db-9c75-9b63d2e720c6 · outbound

This paper cites an unresolved cited work.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Unresolved cited work

Reference 5

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Observation f455a677-72b8-43c7-9de9-95c37be8a502 · outbound

This paper cites Beyond local sharpness: Communication-efficient global sharpness-aware minimization for federated learning.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Beyond local sharpness: Communication-efficient global sharpness-aware minimization for federated learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.784325Z

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Observation f7c5d364-69b5-4966-a16d-61c2f6e9cb2d · outbound

This paper cites Entropy-SGD: Biasing Gradient Descent Into Wide Valleys.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Entropy-SGD: Biasing Gradient Descent Into Wide Valleys

Reference 7

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Observation d13d4e1e-2f8b-4ed4-a064-ec775f96c794 · outbound

This paper cites Parle: parallelizing stochastic gradient descent.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Parle: parallelizing stochastic gradient descent

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:12:35.925622Z

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Observation c77cb239-3a92-4957-a2ae-48805c029d3b · outbound

This paper cites Diffusive G ibbs sampling.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Diffusive G ibbs sampling

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.763818Z

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Observation fdc14fa1-414c-4714-9b04-77dd8328d4d0 · outbound

This paper cites Improved analysis for a proximal algorithm for sampling.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Improved analysis for a proximal algorithm for sampling

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.746971Z

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Observation 7e62e66b-1266-4213-8e91-c98a072631ea · outbound

This paper cites Convergence rate in a nonlinear two-time-scale stochastic approximation with state (time)-dependence.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Convergence rate in a nonlinear two-time-scale stochastic approximation with state (time)-dependence

Reference 11

Resolution: verified exact; doi, observed 2026-08-05T11:12:35.557489Z

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Observation 5e2369b0-0bdd-49d0-827a-d6b065693f34 · outbound

This paper cites An iterative thresholding algorithm for linear inverse problems with a sparsity constraint.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization An iterative thresholding algorithm for linear inverse problems with a sparsity constraint

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.726809Z

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Observation f2e0e66f-168e-464a-ba42-6cfe5d468fa3 · outbound

This paper cites Grawa: Gradient-based weighted averaging for distributed training of deep learning models.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Grawa: Gradient-based weighted averaging for distributed training of deep learning models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.705341Z

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Observation 4206ee04-ccb7-4e0a-b235-0b9accac35c4 · outbound

This paper cites an unresolved cited work.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Unresolved cited work

Reference 14

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Observation 7d6c3149-f13f-4249-8046-3c69e9321a8d · outbound

This paper cites Efficient sharpness-aware minimization for improved training of neural networks.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Efficient sharpness-aware minimization for improved training of neural networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.681019Z

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Observation 22707330-89f0-4c17-80f4-49a7c83b4077 · outbound

This paper cites Locally estimated global perturbations are better than local perturbations for federated sharpness-aware minimization.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Locally estimated global perturbations are better than local perturbations for federated sharpness-aware minimization

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.661064Z

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Observation fa12d06b-cbb3-4b9f-b446-68f7077adf3b · outbound

This paper cites an unresolved cited work.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Unresolved cited work

Reference 17

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Observation 65dabd30-2b79-40a4-b980-a3d632b10ee6 · outbound

This paper cites Sharpness-Aware Minimization for Efficiently Improving Generalization.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Sharpness-Aware Minimization for Efficiently Improving Generalization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T11:12:35.236623Z

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Observation f83a943e-d5f8-4ba6-b4f3-704cd3d30631 · outbound

This paper cites Willard Gibbs.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Willard Gibbs

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.620959Z

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Observation a0b231e1-100e-4936-bd57-9f4a98f1c539 · outbound

This paper cites an unresolved cited work.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:36.597982Z

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Observation 17cd3d59-b9dd-485b-a1d5-c851cf22cd3e · outbound

This paper cites Deep residual learning for image recognition.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Deep residual learning for image recognition

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T11:12:35.275581Z

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Observation e85090fd-7afc-43d9-bbb7-2c3e11332090 · outbound

This paper cites Flat minima.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Flat minima

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.567029Z

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Observation 742f9dce-caa4-4504-b5f0-6094eea7387b · outbound

This paper cites Reverse diffusion monte carlo.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Reverse diffusion monte carlo

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.547539Z

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Observation e1cc1aac-2f20-465a-b100-5a13141f789c · outbound

This paper cites Asynchronous Sharpness-Aware Minimization For Fast and Accurate Deep Learning.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Asynchronous Sharpness-Aware Minimization For Fast and Accurate Deep Learning

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:12:35.696332Z

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Observation a9c60d60-9229-44ac-beb2-f72baaa4b16b · outbound

This paper cites On large-batch training for deep learning: Generalization gap and sharp minima.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization On large-batch training for deep learning: Generalization gap and sharp minima

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T11:12:35.299285Z

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Observation 1e56adeb-6150-463b-b24a-0379b1d990f4 · outbound

This paper cites Smooth minima: A convex relaxation framework for optimizing flatness.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Smooth minima: A convex relaxation framework for optimizing flatness

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.517876Z

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Observation 42d1195c-a7a2-4167-a97c-56c23ef5cd2e · outbound

This paper cites Adam: A method for stochastic optimization.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Adam: A method for stochastic optimization

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.499642Z

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Observation ff6206ee-7c99-40e8-b170-d8d4781f1151 · outbound

This paper cites Learning multiple layers of features from tiny images.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Learning multiple layers of features from tiny images

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.482056Z

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Observation 7a889a4d-dd39-4218-a1d5-24882207738a · outbound

This paper cites an unresolved cited work.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:36.461902Z

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Observation aa3ec2d4-514f-4339-9627-15db32027d00 · outbound

This paper cites Asam: Adaptive sharpness-aware minimization for scale-invariant learning of deep neural networks.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Asam: Adaptive sharpness-aware minimization for scale-invariant learning of deep neural networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.439894Z

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Observation 483e598b-2413-4203-8a37-5e648200ba9e · outbound

This paper cites Gradient-based learning applied to document recognition.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Gradient-based learning applied to document recognition

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-05T11:12:35.331502Z

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Observation 8b212376-ace6-4622-a39f-21dc1b90b358 · outbound

This paper cites Structured logconcave sampling with a restricted gaussian oracle.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Structured logconcave sampling with a restricted gaussian oracle

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.417423Z

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Observation 6796fb7b-1a09-44d9-be80-cc7f967f4e44 · outbound

This paper cites Entropy- MCMC : Sampling from flat basins with ease.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Entropy- MCMC : Sampling from flat basins with ease

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.396433Z

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Observation b19c4ad3-8815-4b43-8caa-d14c2d46e277 · outbound

This paper cites Friendly sharpness-aware minimization.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Friendly sharpness-aware minimization

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.372760Z

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Observation a90be5dc-f873-4e5a-bffd-702a79f75de2 · outbound

This paper cites Towards Efficient and Scalable Sharpness-Aware Minimization.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Towards Efficient and Scalable Sharpness-Aware Minimization

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:12:35.672005Z

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Observation 247f9712-ccdc-4f40-a263-cf067f23e08d · outbound

This paper cites Rosenbluth, Marshall N.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Rosenbluth, Marshall N

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.352128Z

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Observation 068122ec-b5c0-4d92-af7c-74b91d8ee50d · outbound

This paper cites an unresolved cited work.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Unresolved cited work

Reference 37

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Observation a9a83767-34ec-4111-a0dc-46a41b517deb · outbound

This paper cites A method for solving a convex programming problem with convergence rate \( O (1/k^2)\).

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization A method for solving a convex programming problem with convergence rate \( O (1/k^2)\)

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.327230Z

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Observation 16e9b678-3739-4db8-a479-43b68e341217 · outbound

This paper cites Bissacco, Bo Wu, and A.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Bissacco, Bo Wu, and A

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.300563Z

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Observation 6f42480e-51f6-4308-b4d6-dbee95282589 · outbound

This paper cites Exploring generalization in deep learning.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Exploring generalization in deep learning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.278408Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ebe8c6cf-d938-42d9-ab03-e4d9bf40511b · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Pytorch: An imperative style, high-performance deep learning library

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.256105Z

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Observation 20380170-9d3b-4f52-8a48-7b9a933f8853 · outbound

This paper cites Generalized federated learning via sharpness aware minimization.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Generalized federated learning via sharpness aware minimization

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.233915Z

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Observation 5654c2ec-641d-4a45-90a6-df7490a0d070 · outbound

This paper cites Flatsam: Federated learning with sharpness-aware minimization.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Flatsam: Federated learning with sharpness-aware minimization

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.209994Z

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Observation b3c47585-3f6c-444a-8a13-9abb9e1562c3 · outbound

This paper cites Practical sharpness-aware minimization cannot converge all the way to optima.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Practical sharpness-aware minimization cannot converge all the way to optima

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.191229Z

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Observation b57801da-6cd3-4f61-b067-dbdeb21a499b · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 45

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Observation 68c230e0-0038-4fdb-94fe-14126b1329ae · outbound

This paper cites AdaSAM: Boosting Sharpness-Aware Minimization with Adaptive Learning Rate and Momentum for Training Deep Neural Networks.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization AdaSAM: Boosting Sharpness-Aware Minimization with Adaptive Learning Rate and Momentum for Training Deep Neural Networks

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-05T11:12:35.420761Z

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Observation 37c7c8ef-994c-4752-aa08-8d4c6d698cd6 · outbound

This paper cites Dynamic regularized sharpness aware minimization in federated learning: approaching global consistency and smooth landscape.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Dynamic regularized sharpness aware minimization in federated learning: approaching global consistency and smooth landscape

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.170202Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9bd94ccf-889b-4bec-9ace-283d035c7418 · outbound

This paper cites an unresolved cited work.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Unresolved cited work

Reference 48

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:36.147175Z

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Observation fae060c1-0980-40d2-a279-d362bcc66190 · outbound

This paper cites Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models: Extension.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models: Extension

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:12:35.607516Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4153f3d2-b714-4f1c-8e82-3ef19471ee3a · outbound

This paper cites Bayesian learning via stochastic gradient langevin dynamics.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Bayesian learning via stochastic gradient langevin dynamics

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.129162Z

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Observation 385e237f-36d3-4e99-a174-4a74ffb1b170 · outbound

This paper cites How sharpness-aware minimization minimizes sharpness? In The Eleventh International Conference on Learning Representations, 2023 a.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization How sharpness-aware minimization minimizes sharpness? In The Eleventh International Conference on Learning Representations, 2023 a

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:36.105417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 99f44950-fad9-4dc0-90d6-7e4df458e5d2 · outbound

This paper cites Sharpness-aware minimization revisited: Weighted sharpness as a regularization term.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Sharpness-aware minimization revisited: Weighted sharpness as a regularization term

Reference 52

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Observation 873100ee-0551-43d5-b262-29b2cc9f45a3 · outbound

This paper cites Adan: Adaptive nesterov momentum algorithm for faster optimizing deep models.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Adan: Adaptive nesterov momentum algorithm for faster optimizing deep models

Reference 53

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Observation 7fdd96b6-38aa-4200-9920-9b8a3d07929c · outbound

This paper cites Wide Residual Networks.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Wide Residual Networks

Reference 54

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Observation 22469141-0b9b-49ee-bc6d-cb70dda5db2e · outbound

This paper cites mixup: Beyond empirical risk minimization.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization mixup: Beyond empirical risk minimization

Reference 55

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Observation 61b2bd6a-ad3a-4cb8-a143-0e7bdc693044 · outbound

This paper cites Zhang, A.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Zhang, A

Reference 56

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This paper cites Diffusion-based adversarial training produces robust models.

LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization Diffusion-based adversarial training produces robust models

Reference 57

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