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Paper Citation Record · LEDGER

Training Noise Token Pruning

As of 14 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2411.18092.

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

pith.paper-citation-record.v1
2411.18092 v2

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:37:55.528782Z

measured 22 of 22 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 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

22 of 22 outbound references displayed

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  • verified fuzzy11
  • unresolved10
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 77939b07-84dd-4a7a-935c-e55c0db2f450 · outbound

This paper cites Deep Variational Information Bottleneck.

Training Noise Token Pruning Deep Variational Information Bottleneck

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:37:55.435638Z digest=sha256:df9f7bed16eeae9a8913ac13b0b3c723044dcc8d568f46ff092f6714affbea27

Observation b74d0c2a-0cf7-48c2-9332-db170e35f881 · outbound

This paper cites Computation of channel capacity and rate- distortion functions.

Training Noise Token Pruning Computation of channel capacity and rate- distortion functions

Reference 2

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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.

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Observation 2a01516a-bdb2-4679-9c36-7cf85d3338ff · outbound

This paper cites Token merging for fast sta- ble diffusion.

Training Noise Token Pruning Token merging for fast sta- ble diffusion

Reference 3

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

source=pdf_text observed=2026-08-12T11:37:55.446140Z digest=sha256:5a4e661924bb3f229b59ad9c552d93708a8d75a3dc49dd7f59b024b5592f504f

Observation a635bddd-4e72-4f24-aa5d-e48390249bc4 · outbound

This paper cites Token Merging: Your ViT But Faster.

Training Noise Token Pruning Token Merging: Your ViT But Faster

Reference 4

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source=pdf_text observed=2026-08-12T11:37:55.450721Z digest=sha256:54c4159c0c6abf5f54727b7458aaf118995a48458e6ddf4a12be7c90ade5ccca

Observation ad10926a-036e-4729-b7fc-4ba2eb6944a6 · outbound

This paper cites Elements of information theory.

Training Noise Token Pruning Elements of information theory

Reference 5

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source=pdf_text observed=2026-08-12T11:37:55.455509Z digest=sha256:bd26df3d2d153fec882ed02df856f28d37e4d16bdecffe13c2a276c0644a0afe

Observation 19c5020e-ad02-4f8f-b02a-b0fb9ef90db5 · outbound

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

Training Noise Token Pruning Imagenet: A large-scale hierarchical image database

Reference 6

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

source=pdf_text observed=2026-08-12T11:37:55.459877Z digest=sha256:1f16b9880a4b1d8ab9f14600ec85e45a19e840cd2870aa0dbf471292ccbf434c

Observation 9f40ade0-efb0-4f36-9666-f12052e757dd · outbound

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

Training Noise Token Pruning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 7

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source=pdf_text observed=2026-08-12T11:37:55.464268Z digest=sha256:c4cd7a63234a725fac3e95ee8420cbe74858930b6168e2fe567ea73ee061f850

Observation 0146119f-ce3e-4691-98c8-26dbd4c29c24 · outbound

This paper cites Adaptive token sampling for efficient vision transformers.

Training Noise Token Pruning Adaptive token sampling for efficient vision transformers

Reference 8

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

source=pdf_text observed=2026-08-12T11:37:55.469133Z digest=sha256:b09430c508493474f766862c18625b9591dd45c6b6b92bcb4b7b455b4a90a434

Observation 2fcd095d-3a63-41b2-8829-c45a817c7c4c · outbound

This paper cites Power-bert: Accelerating bert inference via progres- sive word-vector elimination.

Training Noise Token Pruning Power-bert: Accelerating bert inference via progres- sive word-vector elimination

Reference 9

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

source=pdf_text observed=2026-08-12T11:37:55.473343Z digest=sha256:3b6a9f5a9c4399d94dc39e3fae2c7d72105e09601df4a63c888122234f74ee46

Observation ca446039-b967-49d5-9f06-be2899078c8c · outbound

This paper cites Which tokens to use? investigating token reduction in vision transformers.

Training Noise Token Pruning Which tokens to use? investigating token reduction in vision transformers

Reference 10

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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=2026-08-12T11:37:55.477466Z digest=sha256:73ee91a03d7247fcc1e7cdc98df1cc89574cc06d9c1abb4bcd119690c82e527b

Observation 995f5df0-33a1-4dea-b902-a63c0ef6e474 · outbound

This paper cites Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search.

Training Noise Token Pruning Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search

Reference 11

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source=pdf_text observed=2026-08-12T11:37:55.481635Z digest=sha256:924b3bc31f01ffc5ef50aaf2ea2edbb559b218ccd8cb28ea58ce50c2df9deb9d

Observation 35598284-7c5a-49a8-af66-9ce1cca6acfe · outbound

This paper cites Learned token pruning for transformers.

Training Noise Token Pruning Learned token pruning for transformers

Reference 12

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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.

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Observation 1416ab19-9c89-4010-a2f9-1aea7eb45c8a · outbound

This paper cites Auto-Encoding Variational Bayes.

Training Noise Token Pruning Auto-Encoding Variational Bayes

Reference 13

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source=pdf_text observed=2026-08-12T11:37:55.490385Z digest=sha256:248c093e8cf87f9d9719f9d1ab67e38291935d9ef852139b4190d09d53aea56d

Observation 57d6bcf7-97de-47df-af2e-fe5c3a0cbd10 · outbound

This paper cites Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations.

Training Noise Token Pruning Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 14

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source=pdf_text observed=2026-08-12T11:37:55.494689Z digest=sha256:97770ef7b353055dd3ff7cbb00357e2c229cd7a29a596c3d34f53757f8aa4001

Observation 526a95a1-388a-4b82-a96b-32ad7c0ccbc7 · outbound

This paper cites The pagerank citation ranking: Bringing order to the web.

Training Noise Token Pruning The pagerank citation ranking: Bringing order to the web

Reference 15

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source=pdf_text observed=2026-08-12T11:37:55.499010Z digest=sha256:09de4e1f1763267b0733da4a47d4f65f4de51db86a4407274e191473a818836e

Observation 45dfab83-8f06-430f-8015-59f9b6a1033e · outbound

This paper cites Dynamicvit: Efficient vision trans- formers with dynamic token sparsification.

Training Noise Token Pruning Dynamicvit: Efficient vision trans- formers with dynamic token sparsification

Reference 16

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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=2026-08-12T11:37:55.502999Z digest=sha256:64f51a0d3ee459181f96d57e44744ce09910430585a724a30e37f871be4c24d8

Observation dd735bfc-7338-4b8a-abe9-9d898480c4e1 · outbound

This paper cites The information bottleneck method.

Training Noise Token Pruning The information bottleneck method

Reference 17

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source=pdf_text observed=2026-08-12T11:37:55.507118Z digest=sha256:6abd0e884f77122fadc989e864a68c45c17e73b559614407af9a4fecd98f9ff6

Observation bc6bb1cd-050f-4772-b739-4934a446f0c8 · outbound

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

Training Noise Token Pruning Training data-efficient image transformers & distillation through atten- tion

Reference 18

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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=2026-08-12T11:37:55.512054Z digest=sha256:446c48e21c867f287308c76faeadb333938af9f3efa0ee594e6b7da2829682c0

Observation 1fa4476c-2ed7-4967-8120-0b28381b7ce5 · outbound

This paper cites Attention is all you need.

Training Noise Token Pruning Attention is all you need

Reference 19

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source=pdf_text observed=2026-08-12T11:37:55.516369Z digest=sha256:d72f0abf0d174d980511f689428777821537f52196a1368b39844baded334b0b

Observation 3aa8e526-b52e-44cd-9d03-aa330081a816 · outbound

This paper cites Zero- tprune: Zero-shot token pruning through leveraging of the attention graph in pre-trained transformers.

Training Noise Token Pruning Zero- tprune: Zero-shot token pruning through leveraging of the attention graph in pre-trained transformers

Reference 20

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

source=pdf_text observed=2026-08-12T11:37:55.520546Z digest=sha256:83466caf9ed992b3e1cd3df4d4f08e9476a25e0f39f2f37ec2c418fbfae7e9ed

Observation 3473bb04-f912-4b64-b405-13aa59e36c60 · outbound

This paper cites Evo-vit: Slow-fast token evolution for dynamic vision transformer.

Training Noise Token Pruning Evo-vit: Slow-fast token evolution for dynamic vision transformer

Reference 21

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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=2026-08-12T11:37:55.524597Z digest=sha256:a24e69727bc0583c60ba5a5949bd2b2107ad922979eb2ba4e39f86c4321a8cd5

Observation b110e29c-7bb0-4b0c-8ae1-7303aa730825 · outbound

This paper cites VisionTransformer- WithTNT.

Training Noise Token Pruning VisionTransformer- WithTNT

Reference 22

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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=2026-08-12T11:37:55.528782Z digest=sha256:8cc9dd3c57feb0e4bab8cfb9b6b9f108420a6c65aec66a3565a9439a458ac47a

Pith citing papers

No inbound Pith citation observations are available.