SAFE: Finding Sparse and Flat Minima to Improve Pruning | Paper Citation Record

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This paper cites write newline.

SAFE: Finding Sparse and Flat Minima to Improve Pruning write newline

Reference 1

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This paper cites A modern look at the relationship between sharpness and generalization.

SAFE: Finding Sparse and Flat Minima to Improve Pruning A modern look at the relationship between sharpness and generalization

Reference 2

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This paper cites Z., and Raghunathan, A.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Z., and Raghunathan, A

Reference 3

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Observation 38432d14-5e7f-48b2-b29f-88b690e93ec4 · outbound

This paper cites Sharpness-aware minimization improves language model generalization.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Sharpness-aware minimization improves language model generalization

Reference 4

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This paper cites Adaptive sharpness-aware pruning for robust sparse networks.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Adaptive sharpness-aware pruning for robust sparse networks

Reference 5

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This paper cites and Teboulle, M.

SAFE: Finding Sparse and Flat Minima to Improve Pruning and Teboulle, M

Reference 6

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This paper cites Fast as chita: Neural network pruning with combinatorial optimization.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Fast as chita: Neural network pruning with combinatorial optimization

Reference 7

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This paper cites and Davies, M.

SAFE: Finding Sparse and Flat Minima to Improve Pruning and Davies, M

Reference 8

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This paper cites Distributed optimization and statistical learning via the alternating direction method of multipliers.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Distributed optimization and statistical learning via the alternating direction method of multipliers

Reference 9

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This paper cites J., Leary, C., Maclaurin, D., Necula, G., Paszke, A., Vander P las, J., Wanderman- M ilne, S., and Zhang, Q.

SAFE: Finding Sparse and Flat Minima to Improve Pruning J., Leary, C., Maclaurin, D., Necula, G., Paszke, A., Vander P las, J., Wanderman- M ilne, S., and Zhang, Q

Reference 10

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This paper cites Entropy- SGD : Biasing gradient descent into wide valleys.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Entropy- SGD : Biasing gradient descent into wide valleys

Reference 11

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This paper cites When vision transformers outperform resnets without pre-training or strong data augmentations.

SAFE: Finding Sparse and Flat Minima to Improve Pruning When vision transformers outperform resnets without pre-training or strong data augmentations

Reference 12

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Observation b02a5969-1389-4517-be84-967ff702b303 · outbound

This paper cites S., and Elsen, E.

SAFE: Finding Sparse and Flat Minima to Improve Pruning S., and Elsen, E

Reference 13

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Observation 1f185cd3-f781-433f-819d-1dcffb8ca218 · outbound

This paper cites Sharpness-aware minimization for efficiently improving generalization.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Sharpness-aware minimization for efficiently improving generalization

Reference 14

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This paper cites and Carbin, M.

SAFE: Finding Sparse and Flat Minima to Improve Pruning and Carbin, M

Reference 15

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This paper cites and Alistarh, D.

SAFE: Finding Sparse and Flat Minima to Improve Pruning and Alistarh, D

Reference 16

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This paper cites and Alistarh, D.

SAFE: Finding Sparse and Flat Minima to Improve Pruning and Alistarh, D

Reference 17

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This paper cites J., Bengio, Y., and Courville, A.

SAFE: Finding Sparse and Flat Minima to Improve Pruning J., Bengio, Y., and Courville, A

Reference 18

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This paper cites Learning both weights and connections for efficient neural network.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Learning both weights and connections for efficient neural network

Reference 19

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This paper cites and Stork, D.

SAFE: Finding Sparse and Flat Minima to Improve Pruning and Stork, D

Reference 20

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This paper cites Deep residual learning for image recognition.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Deep residual learning for image recognition

Reference 21

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Observation fdcbcd0b-b2f6-4f0d-a06d-372b3d1aeba5 · outbound

This paper cites Sparse double descent: Where network pruning aggravates overfitting.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Sparse double descent: Where network pruning aggravates overfitting

Reference 22

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This paper cites F lax: A neural network library and ecosystem for JAX , 2023.

SAFE: Finding Sparse and Flat Minima to Improve Pruning F lax: A neural network library and ecosystem for JAX , 2023

Reference 23

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This paper cites and Dietterich, T.

SAFE: Finding Sparse and Flat Minima to Improve Pruning and Dietterich, T

Reference 24

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This paper cites Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks

Reference 25

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This paper cites Alternating direction method of multipliers for quantization.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Alternating direction method of multipliers for quantization

Reference 26

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This paper cites Accelerated sparse neural training: A provable and efficient method to find n: m transposable masks.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Accelerated sparse neural training: A provable and efficient method to find n: m transposable masks

Reference 27

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Observation d683a92e-9e10-4cf2-9f7d-919dcde611e3 · outbound

This paper cites Averaging weights leads to wider optima and better generalization.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Averaging weights leads to wider optima and better generalization

Reference 28

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This paper cites Fantastic generalization measures and where to find them.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Fantastic generalization measures and where to find them

Reference 29

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This paper cites Fantastic generalization measures and where to find them.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Fantastic generalization measures and where to find them

Reference 30

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This paper cites S., Mudigere, D., Nocedal, J., Smelyanskiy, M., and Tang, P.

SAFE: Finding Sparse and Flat Minima to Improve Pruning S., Mudigere, D., Nocedal, J., Smelyanskiy, M., and Tang, P

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.866528Z

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This paper cites D., Luong, H.-C., Mordukhovich, B.

SAFE: Finding Sparse and Flat Minima to Improve Pruning D., Luong, H.-C., Mordukhovich, B

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.855608Z

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SAFE: Finding Sparse and Flat Minima to Improve Pruning Unresolved cited work

Reference 33

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Observation cd2dd0a0-0206-480d-99cc-40c6a5e161bf · outbound

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

SAFE: Finding Sparse and Flat Minima to Improve Pruning Learning multiple layers of features from tiny images

Reference 34

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This paper cites and Alistarh, D.

SAFE: Finding Sparse and Flat Minima to Improve Pruning and Alistarh, D

Reference 35

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Observation 914f7f97-a8a2-4e75-add0-349cc7ed73d1 · outbound

This paper cites Soft threshold weight reparameterization for learnable sparsity.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Soft threshold weight reparameterization for learnable sparsity

Reference 36

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This paper cites W., Hassoun, J., Keutzer, K., and Gholami, A.

SAFE: Finding Sparse and Flat Minima to Improve Pruning W., Hassoun, J., Keutzer, K., and Gholami, A

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.811476Z

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This paper cites Optimal brain damage.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Optimal brain damage

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.801782Z

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Observation 48faae49-d6d0-4d8c-953c-9f81a32f5f06 · outbound

This paper cites Snip: Single-shot network pruning based on connection sensitivity.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Snip: Single-shot network pruning based on connection sensitivity

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.792052Z

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Observation ce035658-df85-47c8-bd9c-efa20c421512 · outbound

This paper cites Understanding the effects of data parallelism and sparsity on neural network training.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Understanding the effects of data parallelism and sparsity on neural network training

Reference 40

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This paper cites Visualizing the loss landscape of neural nets.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Visualizing the loss landscape of neural nets

Reference 41

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Observation db9b4317-0a56-4202-8aa0-e47a4bd4169d · outbound

This paper cites U., Barba, L., Dmitriev, D., and Jaggi, M.

SAFE: Finding Sparse and Flat Minima to Improve Pruning U., Barba, L., Dmitriev, D., and Jaggi, M

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.762659Z

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Observation c7b381fa-90ed-46fd-a5c1-ba927f62af75 · outbound

This paper cites A survey of lottery ticket hypothesis.

SAFE: Finding Sparse and Flat Minima to Improve Pruning A survey of lottery ticket hypothesis

Reference 43

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Observation 7dae7675-3517-4f9e-87fe-d3fe73baf048 · outbound

This paper cites Rethinking the value of network pruning.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Rethinking the value of network pruning

Reference 44

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Observation 4808e59f-744c-465b-a477-40b92ecc9052 · outbound

This paper cites Alps: Improved optimization for highly sparse one-shot pruning for large language models.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Alps: Improved optimization for highly sparse one-shot pruning for large language models

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.732794Z

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This paper cites Pointer sentinel mixture models.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Pointer sentinel mixture models

Reference 46

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Observation 7dbf8c98-8ce8-4f63-8c9d-78b0209ea6b2 · outbound

This paper cites The llama 3 herd of models.

SAFE: Finding Sparse and Flat Minima to Improve Pruning The llama 3 herd of models

Reference 47

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This paper cites V., and Strubell, E.

SAFE: Finding Sparse and Flat Minima to Improve Pruning V., and Strubell, E

Reference 48

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Observation c995e444-c04d-451a-8050-b4453c312bd6 · outbound

This paper cites M., and Ma, T.

SAFE: Finding Sparse and Flat Minima to Improve Pruning M., and Ma, T

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.691650Z

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Observation 49b4c32e-db84-43a6-bf86-00dcf5d71bb3 · outbound

This paper cites Exploring generalization in deep learning.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Exploring generalization in deep learning

Reference 50

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Observation 6f2f5fa3-eb84-494e-b19e-be746dc338f2 · outbound

This paper cites Anticorrelated noise injection for improved generalization.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Anticorrelated noise injection for improved generalization

Reference 51

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

SAFE: Finding Sparse and Flat Minima to Improve Pruning Pytorch: An imperative style, high-performance deep learning library

Reference 52

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This paper cites Ac/dc: Alternating compressed/decompressed training of deep neural networks.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Ac/dc: Alternating compressed/decompressed training of deep neural networks

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.647342Z

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Observation a2315789-944f-4812-9984-27787c09593d · outbound

This paper cites H., and Alistarh, D.

SAFE: Finding Sparse and Flat Minima to Improve Pruning H., and Alistarh, D

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.636156Z

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SAFE: Finding Sparse and Flat Minima to Improve Pruning Unresolved cited work

Reference 55

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This paper cites What's hidden in a randomly weighted neural network? CVPR, 2020.

SAFE: Finding Sparse and Flat Minima to Improve Pruning What's hidden in a randomly weighted neural network? CVPR, 2020

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.619280Z

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Observation e8c85cd1-3bfd-4ca1-826f-2a4b0c03ab38 · outbound

This paper cites Movement pruning: Adaptive sparsity by fine-tuning.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Movement pruning: Adaptive sparsity by fine-tuning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.608587Z

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Observation 437a1b9d-e318-4682-9d57-5d385878a7e9 · outbound

This paper cites Rethinking pruning large language models: Benefits and pitfalls of reconstruction error minimization.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Rethinking pruning large language models: Benefits and pitfalls of reconstruction error minimization

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.598038Z

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This paper cites Critical influence of overparameterization on sharpness-aware minimization.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Critical influence of overparameterization on sharpness-aware minimization

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.586218Z

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Observation a2246775-aaba-4da4-9486-61d3d2364010 · outbound

This paper cites Very deep convolutional networks for large-scale image recognition.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Very deep convolutional networks for large-scale image recognition

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.575510Z

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Observation db3e5053-86a7-4dcf-ad36-8b8807997524 · outbound

This paper cites Learning from noisy labels with deep neural networks: A survey.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Learning from noisy labels with deep neural networks: A survey

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.563874Z

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Observation d4ab15e2-dcba-460b-8c6a-c87477f33ebc · outbound

This paper cites an unresolved cited work.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:54:53.552637Z

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Observation c5cefda8-e8a3-417b-82a2-d7e5877ef675 · outbound

This paper cites Intriguing properties of neural networks.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Intriguing properties of neural networks

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.541076Z

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Observation 449f3497-e793-4c99-898e-cee3f8deabe1 · outbound

This paper cites L., and Ganguli, S.

SAFE: Finding Sparse and Flat Minima to Improve Pruning L., and Ganguli, S

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.529037Z

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 ae737968-4a0a-40ef-b5a1-81f4ac49f106 · outbound

This paper cites Regression shrinkage and selection via the lasso.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Regression shrinkage and selection via the lasso

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.518428Z

Source-reported events for the cited work

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Observation e9bf8bc5-bc1c-49e0-94b5-f178a8846824 · outbound

This paper cites Llama 2: Open foundation and fine-tuned chat models.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Llama 2: Open foundation and fine-tuned chat models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T05:54:53.337020Z

Source-reported events for the cited work

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Observation b97ef8ab-92c2-4354-8048-b27e97230a0d · outbound

This paper cites Picking winning tickets before training by preserving gradient flow.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Picking winning tickets before training by preserving gradient flow

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.500454Z

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 b023924f-5567-4c06-94d2-c6fe3d286ca3 · outbound

This paper cites Global convergence of admm in nonconvex nonsmooth optimization.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Global convergence of admm in nonconvex nonsmooth optimization

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.490464Z

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Observation 3054c454-15bb-430f-9a9d-b20e9f67df00 · outbound

This paper cites Sharpness-aware minimization alone can improve adversarial robustness.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Sharpness-aware minimization alone can improve adversarial robustness

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.480205Z

Source-reported events for the cited work

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Observation 664e258b-c2dc-4ea9-b503-83da91a44955 · outbound

This paper cites L., Gugger, S., Drame, M., Lhoest, Q., and Rush, A.

SAFE: Finding Sparse and Flat Minima to Improve Pruning L., Gugger, S., Drame, M., Lhoest, Q., and Rush, A

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.470128Z

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 fa503f1e-fc7b-41e0-a5a4-1d1c61f2fa83 · outbound

This paper cites and Urtasun, R.

SAFE: Finding Sparse and Flat Minima to Improve Pruning and Urtasun, R

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.459502Z

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 b721a041-5010-44f2-b932-449a882b8335 · outbound

This paper cites A systematic dnn weight pruning framework using alternating direction method of multipliers.

SAFE: Finding Sparse and Flat Minima to Improve Pruning A systematic dnn weight pruning framework using alternating direction method of multipliers

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.447846Z

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 85cc152d-9203-4f72-94b2-5d1ce8fcc7ba · outbound

This paper cites On the duality between sharpness-aware minimization and adversarial training.

SAFE: Finding Sparse and Flat Minima to Improve Pruning On the duality between sharpness-aware minimization and adversarial training

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.436893Z

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 7f44f5ef-6cb3-43cb-b1d7-0d6115506146 · outbound

This paper cites an unresolved cited work.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:54:53.425964Z

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 e6463e89-eeae-4812-bf85-1b2fb027f27f · outbound

This paper cites Effective sparsification of neural networks with global sparsity constraint.

SAFE: Finding Sparse and Flat Minima to Improve Pruning Effective sparsification of neural networks with global sparsity constraint

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.415378Z

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 a0aaae67-e3f9-483c-a303-91d386177cfa · outbound

This paper cites and Gupta, S.

SAFE: Finding Sparse and Flat Minima to Improve Pruning and Gupta, S

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:54:53.403660Z

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