Pith. sign in

Paper Citation Record · LEDGER

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition

As of 15 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2411.09816.

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

pith.paper-citation-record.v1
2411.09816 v6

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:22:43.753540Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:07:18.824996Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:07:20.818411Z

Reference resolution

35 of 35 outbound references displayed

  • verified exact6
  • verified fuzzy9
  • unresolved20
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 46abba2e-a388-4126-a101-33d6bbd11783 · outbound

This paper cites Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.581723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.581723Z digest=sha256:0128a489e10523bbe9700fa5ce8a451713568b955fe42c1fefbae6d1a5320276

Observation 2985e36f-9222-4db7-a991-ca76a87cb4d8 · outbound

This paper cites Net2Net: Accelerating Learning via Knowledge Transfer.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Net2Net: Accelerating Learning via Knowledge Transfer

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.587757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.587757Z digest=sha256:4197152f01cbe3b19a19251c99fde181dd4040da592a5baa2efdccf66d7598e8

Observation 68b1ee71-d573-4453-bc09-1ef64faec237 · outbound

This paper cites A Survey of Model Compression and Acceleration for Deep Neural Networks.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.594335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.594335Z digest=sha256:72c290fdd656bb08a0807ed90507070f53dfc86a0c93bbaae06d2c0e007d716b

Observation b35ccde5-f87a-4dde-86ef-93e50f5c323d · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Imagenet: A large-scale hierarchical image database

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:22:44.389859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.599597Z digest=sha256:1fed3cf1274e0726fe1f684ddefd3511a75f7e60eb598dc1e79114792ff1401d

Observation 90e56b36-1887-42c8-be0e-f5802f32ae68 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.604545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.604545Z digest=sha256:3f477e57be9b15cd633e780b8b324f8cf232afc88340a4cc9e5174b5a60d58b3

Observation aceb3a6c-7151-426a-a5a4-2333df4037cb · outbound

This paper cites Structured Multi-Hashing for Model Compression.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Structured Multi-Hashing for Model Compression

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-12T20:22:44.125773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.609777Z digest=sha256:ccd37dd3bab3894a360d4c06674b0c4c29a8fe5355c17fe64f5f1b08c32ac7b3

Observation f159c5b0-9b91-4ac1-8cc2-e9810d49503f · outbound

This paper cites Rigging the Lottery: Making All Tickets Winners.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Rigging the Lottery: Making All Tickets Winners

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.615659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.615659Z digest=sha256:e6b821d01a2547d88afaff4d757de6e1cc55b58e8efa9cf3056f0a6b982d2df0

Observation 80e2e3f7-0271-4ae9-bba3-78587960d69b · outbound

This paper cites GradMax: Growing Neural Networks using Gradient Information.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition GradMax: Growing Neural Networks using Gradient Information

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.620521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.620521Z digest=sha256:79f57048b6f9da4fc3460aa8058d111cce414f24f71446adec1c8804b66081db

Observation 304b63d5-8303-4525-8a40-77c78770f44a · outbound

This paper cites Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.625597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.625597Z digest=sha256:075309492610dd52b9f9d43b010e928d13492c74e1f9dffae6c2a37bcfae095a

Observation c268e351-d8fc-4a38-b105-54b4645adf36 · outbound

This paper cites Distilling the knowledge in a neural network.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Distilling the knowledge in a neural network

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:22:44.372417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.630804Z digest=sha256:82e74a4804412432a5a1808eed9ef54c222f2c8da30a0bb7dc0f3212d7fcb9b1

Observation 1711f637-1a21-424a-8050-0b95a30920b5 · outbound

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

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.635783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.635783Z digest=sha256:908d9c94c1a6e4f84ca81a0b26a0b7edbb9cfd699901f6fd1952afa1ce9b90aa

Observation 24ea524c-db5d-43cb-b6fe-ceb5a49c9b51 · outbound

This paper cites Kolda and Brett W.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Kolda and Brett W

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:22:44.355889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.640747Z digest=sha256:0c9e036b53150d728d51a631293df95858d9cb646b951a105c41683a90a2bdb7

Observation 14b3eee8-e4a9-422d-9271-e353dad14a6c · outbound

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

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Learning multiple layers of features from tiny images

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:22:44.339486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.645152Z digest=sha256:16caf250c27fde6a794ecab136b84475466084c916a030d8193e0bb7c6ef7c29

Observation 51f52843-8c2e-4dbe-b511-552794a52e3d · outbound

This paper cites How to Prune Your Language Model: Recovering Accuracy on the "Sparsity May Cry'' Benchmark.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition How to Prune Your Language Model: Recovering Accuracy on the "Sparsity May Cry'' Benchmark

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-12T20:22:44.033760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.649754Z digest=sha256:10a10bc3abdfd659ed9af710ab2feef0e4b9ddfeaca03342ea443abd3949c195

Observation de662480-cb61-4903-bffa-aca07558fcf3 · outbound

This paper cites ALBERT: A Lite BERT for Self-supervised Learning of Language Representations.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.654544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.654544Z digest=sha256:3d2c4a139966bd328a7e5ba81719cf98de5d19734c43d5d010dfb9aacabc4fa0

Observation 5a2fa996-9948-4676-a588-e5313b11e4c5 · outbound

This paper cites Sparsimony - Dynamic sparse training and pruning algorithms for PyTorch , September 2024.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Sparsimony - Dynamic sparse training and pruning algorithms for PyTorch , September 2024

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:22:44.321665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.659338Z digest=sha256:e2dc5dc643717419a0430774a6e36acebefa228f706f4852d0aed6836561a5fd

Observation c1ea1891-a5b5-4edf-a6e8-e199a2a1aa16 · outbound

This paper cites Understanding Parameter Sharing in Transformers.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Understanding Parameter Sharing in Transformers

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-12T20:22:43.988861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.664101Z digest=sha256:51ad1671fb249149d17650729841699574b39b44923b76eea75df7b2d7fee5c7

Observation 34c55d3a-a5eb-418d-9a41-9beb0698d0d9 · outbound

This paper cites DoRA: Weight-Decomposed Low-Rank Adaptation.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.669217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.669217Z digest=sha256:8d0a48572787a0682c153162d70dcc1eaa0a0d7a771ab9adb27934f8053af178

Observation f6da22c0-ce54-4f5b-91e4-de9fe7f87927 · outbound

This paper cites Swin Transformer: Hierarchical Vision Transformer using Shifted Windows.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.674605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.674605Z digest=sha256:e35e0915ad165fc2968325d2fd78fb9620da96fc4d2f0055eee13d965a2dfa08

Observation c47bc98a-4294-424e-b03b-6fcec270f449 · outbound

This paper cites Decoupled Weight Decay Regularization.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Decoupled Weight Decay Regularization

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.679565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.679565Z digest=sha256:2c8dc59e245a7136265dc62cdac20db13b09a6bcf65d5f170836567d384af371

Observation 812f61f9-2dc6-48d7-b666-408f2a44803a · outbound

This paper cites Automated flower classification over a large number of classes.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Automated flower classification over a large number of classes

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:22:44.304112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.684577Z digest=sha256:84fb46947ff495b1c68f37e35ae72415d7b054f40c351f3de2895b37034cb265

Observation c1efe49d-dcfa-4bb5-ba4f-99037eea87af · outbound

This paper cites T-Basis: a Compact Representation for Neural Networks.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition T-Basis: a Compact Representation for Neural Networks

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-12T20:22:43.913887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.689252Z digest=sha256:451c1718ff08a688e4cc7f72904599c8dd7abf55410575630bedb9edb16dc685

Observation 6db621c8-fb4d-4236-acce-d22837245a10 · outbound

This paper cites Parkhi, Andrea Vedaldi, Andrew Zisserman, and C.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Parkhi, Andrea Vedaldi, Andrew Zisserman, and C

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:22:44.288041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.694254Z digest=sha256:83dc637d2b69a8fec10514f44ab011202042f39990669e52ca308c370d84f248

Observation 1f964222-0bc8-4cfb-9c90-75f773ae2d58 · outbound

This paper cites Sparse connection and pruning in large dynamic artificial neural networks.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Sparse connection and pruning in large dynamic artificial neural networks

Reference 24

Resolution
verified exact
doi, observed 2026-08-12T20:22:43.811008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.698878Z digest=sha256:92db25214a1cb78d8d5c7a0b171303a88439a6454bbc9658cce86d3ed32ff2b5

Observation 0514b807-86cc-46dc-86f9-33fae85a10c0 · outbound

This paper cites Lessons on Parameter Sharing across Layers in Transformers.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Lessons on Parameter Sharing across Layers in Transformers

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.703453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.703453Z digest=sha256:9789c03cd38d13111fb9204644644f85c115d74d1f0b2dff96e5fcd30f25ebc9

Observation 34469cd8-71c0-46a0-b630-9aa024448a12 · outbound

This paper cites Evaluating pruning methods.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Evaluating pruning methods

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:22:44.271722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.708207Z digest=sha256:3764d740cc06079ee04e8491525ce67a906c07c787341c23a7443eb2cd87d9d5

Observation f25f8c44-c7ce-4b9f-9c53-7e0faf883d84 · outbound

This paper cites Training data-efficient image transformers & distillation through attention.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Training data-efficient image transformers & distillation through attention

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.713022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.713022Z digest=sha256:ef2687a0e7d923fa2f65fb16a30575d5975fd17cb037b875479d92ecd621a3ae

Observation 9c24d074-f376-41af-937b-5aed07532676 · outbound

This paper cites The inaturalist species classification and detection dataset.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition The inaturalist species classification and detection dataset

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:22:44.254909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.717936Z digest=sha256:1b73f8a83c2eb7448b50503346c9bb6d75dab3b2dbcd58c4d85767ab6a502b55

Observation 6b8804e1-98c4-4cdc-ba84-69cb17404e39 · outbound

This paper cites Compressingtransformers.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Compressingtransformers

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.722447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.722447Z digest=sha256:d6489626a923323666b5ced86fe91e64310d33156dd1c86197ebd7c5776f5887

Observation 2cc2282b-f96c-40ec-91e3-e0d341cb143a · outbound

This paper cites MiniViT: Compressing Vision Transformers with Weight Multiplexing.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition MiniViT: Compressing Vision Transformers with Weight Multiplexing

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-08-12T20:22:43.852292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T20:22:43.727371Z digest=sha256:51aec22c86a8305cb3a19b951258f0f71378c36e64f63181748ff70fd436d19e

Observation 2aa859b4-d1af-48b6-ba11-97036191c7ba · outbound

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

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition To prune, or not to prune: exploring the efficacy of pruning for model compression

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.732391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.732391Z digest=sha256:11cb7f982fd6d3af227e32812d990d1389fe646cc10a350867c6e925f924c3c2

Observation fe20b7c7-4c54-4449-be7e-363869e2474a · outbound

This paper cites write newline.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition write newline

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.737295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.737295Z digest=sha256:92581307d3a9aad6bd7c2b325504c33ff8136ee87fc19be57a68419bae29c14d

Observation 21d0a1d5-a6b6-418f-9106-6d448c17ec4d · outbound

This paper cites @esa (Ref.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition @esa (Ref

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.742874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.742874Z digest=sha256:ccf94768765b9a484db4ed7f722277d7ce1ddb99aaca08e9842b36a176a29d90

Observation c1b41873-cfae-44c2-a9f4-e74770a2614d · outbound

This paper cites an unresolved cited work.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Unresolved cited work

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.748122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.748122Z digest=sha256:c0c218512356661c44c2320b87ee69b362b0ed5953d0a46ea1e1d9bc6711b1bc

Observation 263fec75-f46d-48f6-a7ac-19f0e6969c05 · outbound

This paper cites an unresolved cited work.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition Unresolved cited work

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T20:22:43.753540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:22:43.753540Z digest=sha256:7ee14aaf783f43df854cf81a107dac304cf8a910bca868c142b7006d3699a1d3

Pith citing papers

Observation bcad8d87-ab76-4c8e-96c7-711627e65d0e · inbound

On Information Geometry and Iterative Optimization in Model Compression: Operator Factorization cites this paper.

On Information Geometry and Iterative Optimization in Model Compression: Operator Factorization Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition

Reference 85

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:07:20.894309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:07:18.824996Z digest=sha256:debfacbe76c59a74ad04fee3154957c28314f47d0fe9fb99df9fe9b1d9cd7fff