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Paper Citation Record · LEDGER

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding

As of 11 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2506.11469.

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

pith.paper-citation-record.v1
2506.11469 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:08:24.661127Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

46 of 46 outbound references displayed

  • verified exact1
  • verified fuzzy33
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a24cdab1-b5d1-42bf-b246-6932cbdc5389 · outbound

This paper cites Deep residual learning for image recognition.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Deep residual learning for image recognition

Reference 1

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unresolved
no resolver link, observed 2026-08-07T04:08:20.732806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:20.732806Z digest=sha256:3f6e92f4aad53cb5f40e709da13d2076576ccd77c0ac63cdedef9588e54e4566

Observation 28427626-e53c-4460-99b3-5f1f6fcbfc6e · outbound

This paper cites Spiking-yolo: spiking neural network for energy-efficient object detection.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Spiking-yolo: spiking neural network for energy-efficient object detection

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-07T04:08:31.966553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:20.787943Z digest=sha256:f20aa5521a388707a939c6bd623f207a5dda1af1a405f19fdaa01b85f434379e

Observation 36e63581-1198-447d-ae51-1b90bb4c4850 · outbound

This paper cites Scribblesup: Scribble-supervised convolutional networks for semantic segmentation.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Scribblesup: Scribble-supervised convolutional networks for semantic segmentation

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:31.643777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:20.852828Z digest=sha256:b5080479a6819fbfd27c138892dcc9d5d6a1b4a73f6b856f08280c82d34bdffe

Observation 142aa8b4-9b3b-4952-b1fc-41e8eb9f4f47 · outbound

This paper cites Structadmm: Achieving ultrahigh efficiency in structured pruning for dnns.IEEE transactions on neural networks and learning systems, 33(5):2259–2273, 2021.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Structadmm: Achieving ultrahigh efficiency in structured pruning for dnns.IEEE transactions on neural networks and learning systems, 33(5):2259–2273, 2021

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:31.406388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:20.953393Z digest=sha256:42da01d86f9836e582d51f18df18a758a9db2a2299f1fd8719a3da8825b2a6fd

Observation e6a04cda-4f3c-42db-9826-3129f6c5392a · outbound

This paper cites Convolutional neural network pruning with structural redundancy reduction.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Convolutional neural network pruning with structural redundancy reduction

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-07T04:08:31.052639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:21.060517Z digest=sha256:7ca8c35e0b12badb817cadd641d03593c315b47e911dd1658e27f1bcaf421759

Observation 5af732c4-0d0f-45ad-b6b2-3cf6bee67a00 · outbound

This paper cites Layer Pruning via Fusible Residual Convolutional Block for Deep Neural Networks.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Layer Pruning via Fusible Residual Convolutional Block for Deep Neural Networks

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:08:25.222385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:21.150045Z digest=sha256:5de0d68cb944d401615d7aafa25da42be5b6159ceb6de4f9231839c5abdeac9b

Observation 00d4f95f-d745-4379-b6ef-a33a36338cae · outbound

This paper cites Autocompress: An automatic dnn structured pruning framework for ultra-high compression rates.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Autocompress: An automatic dnn structured pruning framework for ultra-high compression rates

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:30.798205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:21.250947Z digest=sha256:5f7947ad2cac260935d98db8376574020f8135745d85cc473a68b914ae218f98

Observation a7b9e681-c66c-4d1b-b119-3a7a6e3e96fe · outbound

This paper cites Hawq: Hessian aware quantization of neural networks with mixed-precision.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Hawq: Hessian aware quantization of neural networks with mixed-precision

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:30.545904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:21.372170Z digest=sha256:1e504e377219d1cc1c24ae2f376206dd68a0bb54d212cde19709f5933ff41b3d

Observation db61e060-1886-45c7-9430-0373289c97be · outbound

This paper cites Emq: Evolving training-free proxies for automated mixed precision quantization.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Emq: Evolving training-free proxies for automated mixed precision quantization

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:30.244892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:21.479450Z digest=sha256:cdf60aee7c054dc2335b84818e1ee82bce92ea77c5eeeab08827ded2b9e19886

Observation 25a3e048-d2a6-4127-aed6-aa4620e3df89 · outbound

This paper cites Towards unified int8 training for convolutional neural network.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Towards unified int8 training for convolutional neural network

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:29.960623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:21.553022Z digest=sha256:6315727c95ff5160a0e1a7062154aa8cbfe391a60ad68c3fb2009bb8b27df1ef

Observation 4d852df5-85b1-47a6-97ed-2bb888a4e506 · outbound

This paper cites Haq: Hardware-aware automated quantization with mixed precision.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Haq: Hardware-aware automated quantization with mixed precision

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:29.731091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:21.656720Z digest=sha256:bc5763484d9e295944303e7e08260eea3505310219d165c9583567f2751ceaae

Observation 51fbffa3-9255-4305-b39e-246d57d39295 · outbound

This paper cites Teachers do more than teach: Compressing image-to-image models.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Teachers do more than teach: Compressing image-to-image models

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:29.471080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:21.721744Z digest=sha256:d0b882ed0b4a1e093276e4006a8a67538798dd08cc51b768f2dcbcccf03094a9

Observation 3b2ce4cf-0164-487f-b0bd-187b18cb4971 · outbound

This paper cites Relational knowledge distillation.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Relational knowledge distillation

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:29.177324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:21.827916Z digest=sha256:282edca8ed48e71756c30cdfd490afdd5f73ccdfd50f860797e58332663e161c

Observation fba49aa4-6d60-4a6f-b765-283b1c382643 · outbound

This paper cites Knowledge distillation: A survey.Interna- tional journal of computer vision, 129(6):1789–1819, 2021.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Knowledge distillation: A survey.Interna- tional journal of computer vision, 129(6):1789–1819, 2021

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:28.968597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:21.911382Z digest=sha256:ec5a4c482d13e1a86bea6f5afdb37a426dbd638665f55c0da957b2d69ddc8863

Observation 6fac9336-fe9e-4d8f-bb08-8c6a0f5b2af8 · outbound

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

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Channel pruning for accelerating very deep neural networks

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:28.726703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:21.982528Z digest=sha256:8fb4c00b2cb89cb8d5899efa8aa4386f70c1737df41ef8f4d6870a8bd57e1adf

Observation 21b0c78f-fe0c-4a67-9814-99c312f6512c · outbound

This paper cites Thinet: A filter level pruning method for deep neural network compression.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Thinet: A filter level pruning method for deep neural network compression

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:28.537986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:22.050594Z digest=sha256:1edb8cc6dd16fe6520fef9205be1592ce6148f225f614b61d394ced1271bcb8d

Observation 51410e21-9bb7-490b-8c8d-f5e2cf3e8853 · outbound

This paper cites Channel Pruning via Automatic Structure Search.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Channel Pruning via Automatic Structure Search

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:22.127259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:22.127259Z digest=sha256:eb0ba6dea0d15b776e81e9b1878278b4afad27e1450e3c7abe7ff6835c2a2ed0

Observation 2f04d9ad-7f24-48f3-86e9-fb3f64af5d60 · outbound

This paper cites Amc: Automl for model compression and acceleration on mobile devices.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Amc: Automl for model compression and acceleration on mobile devices

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:28.309218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:22.191211Z digest=sha256:1b21db47240cfa140fef60ebd470e020618aa50925b0fb537ee333e99cb867a1

Observation 93367e43-c46b-4403-a06c-0d783ff25a80 · outbound

This paper cites Filter pruning via automatic pruning rate search.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Filter pruning via automatic pruning rate search

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:28.042460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:22.257276Z digest=sha256:76fafbcbf829f13c2f3e7ecff149b938360d7607ec4cc7c23a3666cd2a6c5fd4

Observation aace709f-2a31-4de8-9f63-5bc0e0c8a9f9 · outbound

This paper cites Shufflenet: An extremely efficient convolutional neural network for mobile devices.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Shufflenet: An extremely efficient convolutional neural network for mobile devices

Reference 20

Resolution
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no resolver link, observed 2026-08-07T04:08:22.481427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:22.481427Z digest=sha256:e9cfb2d9c4e8d4036d374d106b881943f70e0ea202b711c0521dc285782a7634

Observation 16ea976e-d288-4f61-8823-4f26dff5031f · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 21

Resolution
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no resolver link, observed 2026-08-07T04:08:22.609705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:22.609705Z digest=sha256:dd276d2513d4413b93244e5c5b62f8596d9f058ce9c848a931258907a3406b2a

Observation a5ce5c5a-8aef-4181-916b-3d5060e57aa8 · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 22

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no resolver link, observed 2026-08-07T04:08:22.681304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:22.681304Z digest=sha256:de40c2bdb86d2d362e0eafcf7e2b0c6559a02a1ead1bd0e9ce6611888f459cc6

Observation daf6c1f3-b2b3-4249-a471-ff47f0dd77f8 · outbound

This paper cites Q-bert: Hessian based ultra low precision quantization of bert.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Q-bert: Hessian based ultra low precision quantization of bert

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:27.660888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:22.744343Z digest=sha256:ad42350ce8fb00fc6cdfd9b208851f3c137e932c98d104d03143c627b8946ac2

Observation 8d476a7e-ab72-404a-b082-25f3b8974d35 · outbound

This paper cites Post-training quantization for vision transformer.Advances in neural information processing systems, 34:28092–28103, 2021.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Post-training quantization for vision transformer.Advances in neural information processing systems, 34:28092–28103, 2021

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:27.356088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:22.823172Z digest=sha256:857e7c87c646f311cfa9d15b8a197bde9db1a42508bbf0e5569eccc483a0bbad

Observation 537139c8-8972-41fe-a937-352b0bd4de9d · outbound

This paper cites Zeroq: A novel zero shot quantization framework.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Zeroq: A novel zero shot quantization framework

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:27.107060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:22.959374Z digest=sha256:1f585c07ba3161946753828be6f0769e5f74fd51925a52f8e718d85cb82d5136

Observation d80d2657-2d6f-472c-ad31-d7fd496e0a08 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Distilling the Knowledge in a Neural Network

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:23.121370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:23.121370Z digest=sha256:e490747a6c4eaa19759e6734d8ce65a79c4168daa6306b19aac181087d589c1f

Observation de03154e-e727-4d30-ab35-86d4ec0ff252 · outbound

This paper cites Contrastive Distillation on Intermediate Representations for Language Model Compression.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Contrastive Distillation on Intermediate Representations for Language Model Compression

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:23.312211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:23.312211Z digest=sha256:ab9524327d8492a33c6964866b50804c634ac35c993350e8bc71648e2d361273

Observation 22a193e8-582a-4cf6-a482-c07bc1dc3252 · outbound

This paper cites Class attention transfer based knowledge distillation.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Class attention transfer based knowledge distillation

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:26.857111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:23.444790Z digest=sha256:9affe6863c1804ed2f4f0c7d2341a8966607913e292d678fa54957d4445dde83

Observation c5fa0439-b385-4f21-b844-e6742715db73 · outbound

This paper cites Exploiting linear structure within convolutional networks for efficient evaluation.Advances in neural information processing systems, 27, 2014.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Exploiting linear structure within convolutional networks for efficient evaluation.Advances in neural information processing systems, 27, 2014

Reference 29

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raw_fallback, observed 2026-08-07T04:08:26.651700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:23.530825Z digest=sha256:89b72b5c3b08d732f425faa2bef20bf478f4738e9d09f2778bbac0a0ae9fb20b

Observation c48aa84c-725a-4492-ae1a-694c00d81eaa · outbound

This paper cites Speeding up Convolutional Neural Networks with Low Rank Expansions.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Speeding up Convolutional Neural Networks with Low Rank Expansions

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:23.609274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:23.609274Z digest=sha256:0c676f1d9ac26aaf3bbd38b72eed1de4ac63d11b956745f9f5e9c489114739ab

Observation 7d567ed1-bebf-4d85-9d3c-f7077e6b0282 · outbound

This paper cites Low-rank matrix factorization for deep neural network training with high-dimensional output targets.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Low-rank matrix factorization for deep neural network training with high-dimensional output targets

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:26.524466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:23.659736Z digest=sha256:0aeaeca21b584224b32d9fbfd75d611e52a5e303982afc3e73c6a560621da21d

Observation 0dd190ba-03c3-4ad7-a8e6-2a2fd6285069 · outbound

This paper cites Pruning filters for efficient convnets.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Pruning filters for efficient convnets

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:26.398868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:23.718032Z digest=sha256:c86158a39de6bf2db3676a913e9c183bb6c68ba3c5c1cb5a9e3f27d8ac5f124d

Observation fd3c3310-7379-4af1-a136-d45904e0f7ea · outbound

This paper cites Hrank: Filter pruning using high-rank feature map.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Hrank: Filter pruning using high-rank feature map

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:26.301799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:23.774050Z digest=sha256:08517939f5d4cc6f160000615d9c0c3df9e0006101cd0885050b85676dc27d9e

Observation d50d9810-d226-44bb-9365-8b5c8fed137e · outbound

This paper cites Learning efficient convolutional networks through network slimming.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Learning efficient convolutional networks through network slimming

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:26.204090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:23.818271Z digest=sha256:c1e447f1a9579cdbd0ab24496fc0fdd47a92a0e2b813018ab4c68a81d498283e

Observation 0347cd0a-8e14-4710-ba2b-c837110c8e77 · outbound

This paper cites Metaprun- ing: Meta learning for automatic neural network channel pruning.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Metaprun- ing: Meta learning for automatic neural network channel pruning

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:26.143530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:23.857463Z digest=sha256:e22c75cf13a51c471de31708b0640ee54ab5cf73cc15a42aba31dfbb02880d27

Observation f1648fb9-3c08-489d-948c-03fa9a2e73b7 · outbound

This paper cites Auto graph encoder-decoder for neural network pruning.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Auto graph encoder-decoder for neural network pruning

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:26.101986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:23.929163Z digest=sha256:861812c424ac558fad29146fe1269b958d53a34f659c1dfb692e01c760344a6c

Observation 67d3db66-2ac1-4aca-a89e-3e13e2bd8322 · outbound

This paper cites Automatic network pruning via hilbert-schmidt independence criterion lasso under information bottleneck principle.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Automatic network pruning via hilbert-schmidt independence criterion lasso under information bottleneck principle

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:25.934861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:23.989661Z digest=sha256:d42eae50fea8921d18311559585070d62dad93a35d3e7ae83f2e77a1e1c1a0b8

Observation 411807dd-0f29-40ce-8b05-aa47fb1f83fd · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Semi-Supervised Classification with Graph Convolutional Networks

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:24.055004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:24.055004Z digest=sha256:fae641be116758b932aec250083e49a3b6f6773a493e9501d4da088de732ab25

Observation 241f12e3-494e-408e-8bab-4d58eb059c39 · outbound

This paper cites Graph Attention Networks.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Graph Attention Networks

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:24.160079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:24.160079Z digest=sha256:bcd2027ad6b07fc588267067a8cd050ab5e9eea84f64ce473da19b57a644c867

Observation eaff2616-1cfe-41bc-b129-f607972fba73 · outbound

This paper cites Graph structure of neural networks.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Graph structure of neural networks

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:25.822856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:24.230220Z digest=sha256:7a74643baa97515fbec8092d856d52c3c15c2173e5730be28e9d60b39fdb1a15

Observation 9113b8fb-26f0-4af0-a911-c08688e245ec · outbound

This paper cites ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:24.275727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:24.275727Z digest=sha256:fa385c0224eb4840ad1394e4767b00baa4d3057ebbb5a19f16f815caa873940d

Observation 31092b71-827b-4f06-8c35-1a4827d457ca · outbound

This paper cites Progressive neural architecture search.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Progressive neural architecture search

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:25.676837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:24.373624Z digest=sha256:200ec1c22f50f350c09a9452a3ca2536626756b8fcf18280964189e6fca62c4f

Observation e9a5e615-fb44-4b96-9b7d-7babe3a3bdc2 · outbound

This paper cites Automl: A survey of the state-of-the-art.Knowledge-based systems, 212:106622, 2021.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Automl: A survey of the state-of-the-art.Knowledge-based systems, 212:106622, 2021

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:24.455375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:24.455375Z digest=sha256:451d09dc964b30d5143f34732ebb1515a10caaf30e3551f671d7dcd261eaf8c9

Observation 37c116b6-1538-461c-a479-518cc05a6808 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding A simple framework for contrastive learning of visual representations

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:25.567173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:24.542323Z digest=sha256:62a2e3bcea9dddd59aa41b8a14cab894141c1ffcbd32b801adbdf6b17afc2ad8

Observation 100400db-b84a-40c4-9134-5226b707a8ee · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Momentum contrast for unsupervised visual representation learning

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:25.477535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:24.593112Z digest=sha256:90ad759c5003c9d56b6839b3cc4e2a748a817de4510353da36feaf402f216707

Observation 8efd827c-6ab4-409c-8b57-ae6cb026045d · outbound

This paper cites Inductive representation learning on large graphs.Advances in neural information processing systems, 30, 2017.

Structure-Aware Automatic Channel Pruning by Searching with Graph Embedding Inductive representation learning on large graphs.Advances in neural information processing systems, 30, 2017

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:08:25.337248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T04:08:24.661127Z digest=sha256:96af327e599f07d169a0c6f89d39a6fa401acda3ca6482a3a5f839c67cbf6e9b

Pith citing papers

No inbound Pith citation observations are available.