Pith. sign in

Paper Citation Record · LEDGER

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference

As of 8 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2507.16260.

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

pith.paper-citation-record.v1
2507.16260 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:19:59.110224Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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 exact2
  • verified fuzzy27
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9af22605-017b-459b-a20c-567cd3042483 · outbound

This paper cites Attention is all you need,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Attention is all you need,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:58.837857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:58.837857Z digest=sha256:0ceb1b7fafaa8d27986ddac13eb8519f20c9b9a2991d07b22c6052db815712ac

Observation 0cc6bdb9-1adf-4c2f-96d5-0deb8ff02b75 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:58.844109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:58.844109Z digest=sha256:8e41d20ccb08dc52176f9786d3cfee5a3fe762fdb065ffa31aab977b0cda290d

Observation 625c183d-304e-478e-ac5a-1e66d08d1c75 · outbound

This paper cites (2022) Introducing chatgpt.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference (2022) Introducing chatgpt

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:00.180963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.853053Z digest=sha256:904e09b7e84cb34939ce0f031438b4c62ea74338c839adfa4c6bcb60fcf7bc2c

Observation 3b0154b0-7f2c-4e98-9df6-d4c2dbb78b5b · outbound

This paper cites (2023) Github copilot: Your ai pair programmer.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference (2023) Github copilot: Your ai pair programmer

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:00.146757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.861119Z digest=sha256:c35684d8eff8e7334e9c51482f8a30b08df12400a6ab8176cadfa4ffca9ac615

Observation 9d22507a-d8a7-4c12-a8a2-e241f0284866 · outbound

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

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Training data-efficient image transformers & distillation through attention,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:58.869022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:58.869022Z digest=sha256:4935e7c159f9406647c314f6a944e744eb6584bd89509d01894486e40e3f5a6f

Observation d2f7a58c-099c-402e-a65f-582dd39f2fee · outbound

This paper cites Tinymim: An empirical study of distilling mim pre-trained models,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Tinymim: An empirical study of distilling mim pre-trained models,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:00.082874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.874879Z digest=sha256:1c63e1316ffad08a9d94d6d77a0b9e0c7e3d7ec639cd20f347384acb485cf892

Observation d587a21c-d107-43c5-a37c-bd25f3be3deb · outbound

This paper cites Llm-pruner: On the structural pruning of large language models,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Llm-pruner: On the structural pruning of large language models,

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:58.882285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:58.882285Z digest=sha256:9b40c6032962692f5777044aad93b1afea7d7e6db2a7bfd399d36b9325a2e96c

Observation 78efd689-fbdd-4af7-a373-282771e77cf3 · outbound

This paper cites Width & depth pruning for vision transformers,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Width & depth pruning for vision transformers,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:00.025120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.888142Z digest=sha256:a9641448ed6607ad88f6d3f15eb42fa57c74d1cb91bc9a755acf8de910fed14b

Observation fe4a3eab-9de8-4e80-ab80-8c3fba1aba3a · outbound

This paper cites Towards accurate post-training quantization for vision transformer,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Towards accurate post-training quantization for vision transformer,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.993363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.894027Z digest=sha256:4e5e1d1b1350bbfb82662c42dfdeb2319d195b0fd94dad06c96a738fe2e9531d

Observation 62356d5e-b19f-4ac8-b4a9-b25d4f2ed401 · outbound

This paper cites Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.972101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.900070Z digest=sha256:0e31afdfae3f41f4f2561629b6b69ec39b02a99450c9bab12746e19177f19397

Observation 19e15b13-674d-47e8-a099-3970fb6770cb · outbound

This paper cites Co-scale conv-attentional image transformers,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Co-scale conv-attentional image transformers,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.952342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.906535Z digest=sha256:f895e75f4ceb71c1a95d145b113e208387a0ad7a7104f640fd2b14533c2735c2

Observation 572eed05-64be-4d63-9395-b1fc0ed5187e · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:58.912103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:58.912103Z digest=sha256:b9b2f66c8cb42622b128367338d68bb7b2b556cb6e11707aa08c42e3361b8276

Observation 5924a9e0-d702-4f04-bc33-fc69fadcd86b · outbound

This paper cites Tokens-to-token vit: Training vision transformers from scratch on imagenet,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Tokens-to-token vit: Training vision transformers from scratch on imagenet,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.916326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.917727Z digest=sha256:b51336518ab34ecc4dd699df8cbb47796d992937af9dade31c79eed7536905ee

Observation 87a9b2e3-3c2f-46d2-94f8-a85bd043f075 · outbound

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

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:58.923885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:58.923885Z digest=sha256:c6b78f38d402b7d250250fcf2a0b5b7bd8e60cb34fad45976d69ad4d6216f24e

Observation e12db6a7-43fa-4d7e-ba8c-f503893a1a2b · outbound

This paper cites Dynam- icvit: Efficient vision transformers with dynamic token sparsification,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Dynam- icvit: Efficient vision transformers with dynamic token sparsification,

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:58.929249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:58.929249Z digest=sha256:80163c60b60aecd4aca39b602eccb7b4bb002265db127b976fdc413991eaf47f

Observation 70cd872a-877b-43c8-8948-f5ab71a62886 · outbound

This paper cites Token merging: Your vit but faster,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Token merging: Your vit but faster,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.873298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.934260Z digest=sha256:9bcae10a0817a6ca7f3b6a02e40f841c1184d4a2a4183e824c0c1ba2d8b3833c

Observation 1f88df41-913b-4475-aacd-ea987b69ac93 · outbound

This paper cites Adaptive sparse vit: towards learnable adaptive token pruning by fully exploiting self-attention,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Adaptive sparse vit: towards learnable adaptive token pruning by fully exploiting self-attention,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.853885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.938965Z digest=sha256:4c31afe08675eb393d5f1d4c31b37a92b0504c820321c00e8197143214218f7e

Observation abacbcaa-26e1-43f2-800d-1412e5f28a1c · outbound

This paper cites A simple romance between multi-exit vision transformer and token reduction,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference A simple romance between multi-exit vision transformer and token reduction,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.831841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.944619Z digest=sha256:dc08d52c89b100bd4ee04125d399a72bc74822e9f5199316a883adec95135416

Observation 832cfb95-3282-47cf-842f-523cf4fa28d0 · outbound

This paper cites Synergistic patch pruning for vision transformer: Unifying intra-& inter-layer patch importance,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Synergistic patch pruning for vision transformer: Unifying intra-& inter-layer patch importance,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.809147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.952328Z digest=sha256:08a903a65d571bfb23d63d96e85253752702fd39f0b729b78b4a4f1cdf1c2e4e

Observation 5a02c8ef-48f5-45be-9de3-930a74b587db · outbound

This paper cites Diffrate: Differentiable compression rate for efficient vision transformers,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Diffrate: Differentiable compression rate for efficient vision transformers,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.784661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.960087Z digest=sha256:367b805cf865c9beade6c2a54916ae7830f0226972619abf9e669ae44162fd01

Observation f2aff503-aa81-4511-8807-d79ad442c39f · outbound

This paper cites Beyond attentive tokens: Incorporating token importance and diversity for efficient vision transformers,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Beyond attentive tokens: Incorporating token importance and diversity for efficient vision transformers,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.759181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.965826Z digest=sha256:fbc12fa8d47de87a09360a66bd8fc04403591b4aff618d05dda91fbb9fb040d6

Observation f77f8566-6718-4936-80e4-fea8cb6fb691 · outbound

This paper cites Joint token pruning and squeezing towards more aggressive compression of vision transformers,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Joint token pruning and squeezing towards more aggressive compression of vision transformers,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.736637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.972638Z digest=sha256:5f004b8cf470b9b9bc71606f73fa7708d1bce1fbbbdce2172dcf5389c25fa10d

Observation 2de641b9-64a4-4e3b-9b16-e1caf65f9fd3 · outbound

This paper cites All Tokens Matter: Token Labeling for Training Better Vision Transformers.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference All Tokens Matter: Token Labeling for Training Better Vision Transformers

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:19:59.317187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.978387Z digest=sha256:3eb19d89c26e6669cb36986e1fa1e0aa42895d6119ca12f1b20c7f431e96aa6b

Observation 5af4db4f-f28f-4827-bbbe-0e19e78aa40e · outbound

This paper cites [Online].

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference [Online]

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.713468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:58.984084Z digest=sha256:a77fd291564ca5a9c3d0db528f4c8bbd5e0798c3bd56b6e14981401aae6abd8f

Observation fb95ba81-c319-4833-95a2-07d6ddd47cfc · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Categorical Reparameterization with Gumbel-Softmax

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:58.990554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:58.990554Z digest=sha256:605f3cc59131b6190304cbe50d8c2d406f92bd0b78eca0df43baee5fa077d4d7

Observation 568dd40d-ccb7-4160-b96e-34cc1a7a87c4 · outbound

This paper cites The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:58.996503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:58.996503Z digest=sha256:ac35488b543ad92a41bac09b8dc38f3edfa0091ce76e8c1fdf8d269c5fbe409b

Observation 4df2c928-24a3-4f30-97a7-78f5eebbe469 · outbound

This paper cites All tokens matter: Token labeling for training better vi- sion transformers,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference All tokens matter: Token labeling for training better vi- sion transformers,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.685878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.001219Z digest=sha256:9737ab0edc17734abd8e296e9a7597a26c0bfd2d5d12db49891ce4b7df868248

Observation 8cc1c5bf-8968-4ad3-9eca-ff44277872a7 · outbound

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

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Imagenet: A large-scale hierarchical image database,

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:59.007173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:59.007173Z digest=sha256:eb99cdcad4ac9adf70076a173371d6a41ac20b0fa26c6c3f7194cbf94e2c1712

Observation cb0d1b08-096d-49d0-aa98-1f546ab89995 · outbound

This paper cites Crossvit: Cross-attention multi- scale vision transformer for image classification,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Crossvit: Cross-attention multi- scale vision transformer for image classification,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.647920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.011938Z digest=sha256:da622703843c4814c2004dfb131a8d324038108d8ffeac61fbbca1fcce5a23fe

Observation 8987f68c-8c40-440b-bc33-52f6ac536e7a · outbound

This paper cites Conditional Positional Encodings for Vision Transformers.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Conditional Positional Encodings for Vision Transformers

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:59.017983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:59.017983Z digest=sha256:fa9663b71a9b12ddce2b1025c5637ec7c47cca20cea60bebf91abcd6d474bd3a

Observation 44b3072c-8fde-4962-9483-13ed35662064 · outbound

This paper cites Designing network design spaces,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Designing network design spaces,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.621790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.024356Z digest=sha256:363201dfe989643d248a373010693c46aa6d3cbaa103d1d2730ed618305529ac

Observation 3d830739-c10d-4ffa-8adb-fb5655c9ef7d · outbound

This paper cites Efficientnet: Rethinking model scaling for con- volutional neural networks,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Efficientnet: Rethinking model scaling for con- volutional neural networks,

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:59.031380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:59.031380Z digest=sha256:b5de0b2a84f819d61b995067d91c0f489b0b0fcaa96ab984c7216b77bc16f536

Observation 97cb1b04-74a3-4c25-b03f-e0aa5e84be7b · outbound

This paper cites High-performance large-scale image recognition without normalization,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference High-performance large-scale image recognition without normalization,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.579909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.036325Z digest=sha256:72676107bd26ea399d578fac7fb5b9b421a7a6bf73eaa67c5872d328beec13ad

Observation e50636b9-6167-4504-b1e4-ca2361d7bfdd · outbound

This paper cites Ia- red2: Interpretability-aware redundancy reduction for vision transform- ers,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Ia- red2: Interpretability-aware redundancy reduction for vision transform- ers,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.551094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.043395Z digest=sha256:b25d9bf6d75b47037825efa6b025a6ea039f66ef07863baeebaef3228e0ac502

Observation d7d8b8ae-3b9a-4682-9082-11b969d85168 · outbound

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

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Evo-vit: Slow-fast token evolution for dynamic vision transformer,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.525469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.049458Z digest=sha256:870ed4d89829a3599bc546509cd771f571396efd206127ebfc680dfc968d5f4b

Observation 8003ba18-028c-4aec-99ff-e69e99ef612e · outbound

This paper cites Token fusion: Bridging the gap between token pruning and token merging,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Token fusion: Bridging the gap between token pruning and token merging,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.502746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.055273Z digest=sha256:e1330bd5af8e3a7619dee7b4b2498690b2cd5ee1e3f106e3c0fc9fe69ff4ed72

Observation a8a5d023-6529-418a-aa39-3c600eb0082a · outbound

This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference An image is worth 16x16 words: Trans- formers for image recognition at scale,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:59.063188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:59.063188Z digest=sha256:581b191a14d27be9a326b5086208cd6f5f6f83ea39fef283b3993b357d04ca4b

Observation 8427ab51-f64f-4175-a580-a259b68060b3 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.465685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.069281Z digest=sha256:15631d67b76e8925d206761a21d786ffde8ff21d87979567d82282fc973aa68d

Observation 1e7d451e-8995-4a7a-9dc5-a7b9369c9f48 · outbound

This paper cites Edge learning: The enabling technology for distributed big data analytics in the edge,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Edge learning: The enabling technology for distributed big data analytics in the edge,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.447360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.075342Z digest=sha256:b14a5dd288519035df43c50b8702262552703cd0eb615dc164eaa7cbc3861bc6

Observation ab0038f8-df86-4fdd-b33f-9d5a946a32a1 · outbound

This paper cites OTAS: An Elastic Transformer Serving System via Token Adaptation.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference OTAS: An Elastic Transformer Serving System via Token Adaptation

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:19:59.217652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.080749Z digest=sha256:872239a11d8b03a9995129e3ad764f1ecdcc5e620f2f9dde2e8fa9a0616c5a13

Observation 43a9069e-a3c9-4aca-b3c6-20f5ad12c821 · outbound

This paper cites Analyzing the Structure of Attention in a Transformer Language Model.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Analyzing the Structure of Attention in a Transformer Language Model

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:59.085751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:59.085751Z digest=sha256:6688277bb67b2af73dcc57eef9cae1de8b20998c8bb9c801740126871020d1e0

Observation d0c9366d-5136-4032-9bc3-3b4c3c06da3c · outbound

This paper cites Xception: Deep learning with depthwise separable convolu- tions,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Xception: Deep learning with depthwise separable convolu- tions,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.426932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.090761Z digest=sha256:64d833428a01cb7146aacc40d375d6bb6c37abd02e27cbf469cfd5ada5b34077

Observation 4a768149-49f9-479c-b834-657140eaa732 · outbound

This paper cites Approximation by superpositions of a sigmoidal function,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Approximation by superpositions of a sigmoidal function,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:59.095202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:59.095202Z digest=sha256:2dee4c882426fbc883db8a3215c8b4355abad2315da86f09d62170d4cd1043a4

Observation c7f1ee75-5fd2-42f4-b9ed-ac79be845217 · outbound

This paper cites Learned Thresholds Token Merging and Pruning for Vision Transformers.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference Learned Thresholds Token Merging and Pruning for Vision Transformers

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:59.099779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:59.099779Z digest=sha256:debce8513a6fb75cd82638ee6f610683e9b75f8ec98953c78cf7d889474729f3

Observation f27f4608-c54d-415f-b3ea-948f73c63830 · outbound

This paper cites PPT: Token Pruning and Pooling for Efficient Vision Transformers.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference PPT: Token Pruning and Pooling for Efficient Vision Transformers

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:59.104941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:59.104941Z digest=sha256:690cb274b503791e9b36a419a0334283c4df8e662c5bf18a8e966697b632aa3b

Observation baa02c17-fe57-444a-9de5-6a628a2ade34 · outbound

This paper cites No token left behind: Efficient vision transformer via dynamic token idling,.

ToFe: Lagged Token Freezing and Reusing for Efficient Vision Transformer Inference No token left behind: Efficient vision transformer via dynamic token idling,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:59.386239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:59.110224Z digest=sha256:ef517f86ab67a68d764906a85676e93ea7b65efb7f7354ab7f4f491648c4da75

Pith citing papers

No inbound Pith citation observations are available.