Paper Citation Record · LEDGER

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification

As of 17 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2508.12891.

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

pith.paper-citation-record.v1
2508.12891 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:22:04.383691Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

verified exact0
verified fuzzy18
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ff66dc0d-cf44-4593-9b0e-39c7b65cc143 · outbound

This paper cites Attention is all you need,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Attention is all you need,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.841208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 279eb89d-9ddd-4735-abde-10058fb717df · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Imagenet classification with deep convolutional neural networks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.827325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 05b3245d-96d9-4aec-9a1a-a4c32267f120 · outbound

This paper cites Deep residual learning for image recognition,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Deep residual learning for image recognition,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.248597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a55ef8a-f1ca-4bb3-a64e-d3cd08a41de8 · outbound

This paper cites Scaling Laws for Neural Language Models.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Scaling Laws for Neural Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.254041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 602836f1-b025-4a06-895e-016727ddbc66 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.258999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6b0f90a-8cb1-4185-a32d-bb17d096eb83 · outbound

This paper cites Quantization and training of neural networks for efficient integer-arithmetic-only inference,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Quantization and training of neural networks for efficient integer-arithmetic-only inference,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.263999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbb0372b-f02b-4312-8c96-89ea162d32e0 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Distilling the Knowledge in a Neural Network

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.269171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae1582f7-f7e6-48de-8a7e-d6cacf09000a · outbound

This paper cites Exploiting linear structure within convolutional networks for efficient evaluation,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Exploiting linear structure within convolutional networks for efficient evaluation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.795480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2ff343e4-f9bc-4f25-a35f-0c1ea07a5eb6 · outbound

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

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Learning both weights and connections for efficient neural network,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.780787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f5844b1f-abc1-4b9e-899e-ed05d0954bbc · outbound

This paper cites Pruning filters for efficient convnets,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Pruning filters for efficient convnets,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.282490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4429e525-740d-407f-8ab8-e1e8895730c2 · outbound

This paper cites Channel pruning for accelerating very deep neural networks,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Channel pruning for accelerating very deep neural networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.757011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 501006e2-bb94-43ba-ae1a-de4e73df36e1 · outbound

This paper cites Learning structured sparsity in deep neural networks,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Learning structured sparsity in deep neural networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.742458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 924576e3-c082-4e45-98a5-0f9949ae4af0 · outbound

This paper cites Dynamic structure pruning for compressing CNNs,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Dynamic structure pruning for compressing CNNs,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.727515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0f2a4b5c-ea90-4723-80a1-43820a8a8d21 · outbound

This paper cites The final data release of ALLSMOG: a survey of CO in typical local low-M* star-forming galaxies.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification The final data release of ALLSMOG: a survey of CO in typical local low-M* star-forming galaxies

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T17:22:04.486119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6ef88264-70e0-44a5-a80b-7e4426ba3b24 · outbound

This paper cites To prune, or not to prune: exploring the efficacy of pruning for model compression.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification To prune, or not to prune: exploring the efficacy of pruning for model compression

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.304613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 258114cf-2307-4f56-a608-d478841e283f · outbound

This paper cites Dynamic model pruning with feedback,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Dynamic model pruning with feedback,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.713695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c5e54d44-b8e1-4313-8f43-33177b6e6649 · outbound

This paper cites Deep rewiring: Training very sparse deep networks,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Deep rewiring: Training very sparse deep networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.699626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 25b167ff-1646-4ddc-9972-531e8f3a33f2 · outbound

This paper cites Soft threshold weight reparameterization for pruning neural networks,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Soft threshold weight reparameterization for pruning neural networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.685118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3127812c-7f6f-4ee8-9da5-87f0200f2191 · outbound

This paper cites Winning the lottery with continuous sparsification,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Winning the lottery with continuous sparsification,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.670182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 767252fa-f6cf-4abc-8a2d-fffb39f4a249 · outbound

This paper cites A Survey on the Robustness of Feature Importance and Counterfactual Explanations.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification A Survey on the Robustness of Feature Importance and Counterfactual Explanations

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.328571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 672954f5-596f-4884-86e0-a3d9ec3b6c08 · outbound

This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification The lottery ticket hypothesis: Finding sparse, trainable neural networks,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.333439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 418ff4aa-1629-454b-8037-c61e5b4a39f0 · outbound

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

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification SNIP: Single-shot network pruning based on connection sensitivity,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.647055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e1b745db-7de2-4748-adfb-1a9484ba0e07 · outbound

This paper cites How I learned to stop worrying and love retraining,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification How I learned to stop worrying and love retraining,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.631711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bccf2270-e619-4a24-9348-f3413018e153 · outbound

This paper cites “Learning-compression.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification “Learning-compression

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.616118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7495c508-e7db-4894-844b-ef34f09808a3 · outbound

This paper cites Global sparse momentum SGD for pruning very deep neural networks,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Global sparse momentum SGD for pruning very deep neural networks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.601292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b7ab55dd-3600-47e9-95e2-11f35bccb7d5 · outbound

This paper cites Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.586967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d6176ce4-a9eb-4590-b006-aae9a6bc3d57 · outbound

This paper cites On the lattices of exact and weakly exact structures.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification On the lattices of exact and weakly exact structures

Reference 27

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T17:22:04.438507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5d9ef1db-307f-48da-97d4-662a1a5eabe0 · outbound

This paper cites Speeding up convolutional neural networks with low rank expansions,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Speeding up convolutional neural networks with low rank expansions,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.572565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 466d5360-b4c8-4074-9aa1-88f3f492e226 · outbound

This paper cites SoLA: Leveraging soft activation sparsity and low-rank decomposition for large language model compres- sion,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification SoLA: Leveraging soft activation sparsity and low-rank decomposition for large language model compres- sion,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:22:04.557784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ef1dbdf5-4892-4985-9fc6-e955b05bef58 · outbound

This paper cites SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.375099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3472470c-9fda-426c-8d26-f186d3ba3618 · outbound

This paper cites Learning the parts of objects by non- negative matrix factorization,.

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Learning the parts of objects by non- negative matrix factorization,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.379438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2804a906-99a9-41a7-8a72-d9a463c6a744 · outbound

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

ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification Learning multiple layers of features from tiny images,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T17:22:04.383691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.