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Paper Citation Record · LEDGER

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers

As of 17 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 2 inbound Pith citation observations for arXiv:2505.21847.

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

pith.paper-citation-record.v1
2505.21847 v2

Coverage vector

measured 75 of 75 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:27:53.028375Z

measured 77 of 77 standing notices

One-hop event checks from named stored sources.

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

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:24:55.763468Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T23:23:15.956970Z

Reference resolution

75 of 75 outbound references displayed

  • verified exact0
  • verified fuzzy56
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9f72e720-c5fe-41da-a60a-1f84b4dd89f4 · outbound

This paper cites Token merging: Your vit but faster.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Token merging: Your vit but faster

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:03.324248Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.005435Z digest=sha256:d49d80999e88a13a6fc614308b29f482106dbb53ede19643c4ca2c9dfcaa277e

Observation e39ff7ba-7241-44d0-8076-3477bb150985 · outbound

This paper cites B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:03.163821Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.078005Z digest=sha256:e061c54282ea08ff47ab51d79a38d74e8a4e60d3d85e5032b683ca592f306900

Observation 46c3df74-c7e2-429a-9732-855b8aacf71e · outbound

This paper cites Efficientvit: Multi-scale linear attention for high-resolution dense prediction.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Efficientvit: Multi-scale linear attention for high-resolution dense prediction

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:02.958549Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.148509Z digest=sha256:fcc67513353a025d10c8da8f4a47d1891d9dc6d94bbce718aceb5f4fd1c73892

Observation 9e66d914-440c-49a4-973b-b5d0fc9adb94 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Emerging properties in self-supervised vision transformers

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:45.217463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:45.217463Z digest=sha256:df794e34b7e46fe6688f5fe2d1fc8502bfb46f04cf7f407fe323142798ecd48e

Observation 100ccb8b-8646-472b-a642-03c32402a6d8 · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:45.287973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:45.287973Z digest=sha256:70b75fcde9f744749912776ef8974abfef647212258b86c67cb403bee369b8e6

Observation 72540cce-a55e-48b5-bd4e-1820d0b6c9d7 · outbound

This paper cites Mobile-former: Bridging mobilenet and transformer.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Mobile-former: Bridging mobilenet and transformer

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:02.852775Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.357089Z digest=sha256:711da4fd38ce6009c77de4359362302887a42c7aa6c596db14cb9afa50beeb8f

Observation f21975cf-6cef-4b0b-99db-7fae7383546c · outbound

This paper cites Improved feature distillation via projector ensemble.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Improved feature distillation via projector ensemble

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:02.708513Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.439229Z digest=sha256:65bc65d27be0e2e7a055c09a875536e66143e3df00e7d415e9559fa78783f564

Observation 885c1f45-f0dc-4280-9185-2a5d07d83883 · outbound

This paper cites Reproducible scaling laws for contrastive language-image learning.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Reproducible scaling laws for contrastive language-image learning

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:02.522153Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.505134Z digest=sha256:e910c7ddee637e886b12658d6fdd14034ab455871a3e163782ebf02bc204327d

Observation 141a2893-5439-4802-b290-ca7940c93b5d · outbound

This paper cites MMSegmentation : Openmmlab semantic segmentation toolbox and benchmark.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers MMSegmentation : Openmmlab semantic segmentation toolbox and benchmark

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:02.402922Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.556904Z digest=sha256:05fc04d63e16deef498de2d80dfa85fbdea91a45ffe1dc9f2e2d5e6505246979

Observation 208860e0-422c-4ad6-8577-283af8f730df · outbound

This paper cites Flashattention: Fast and memory-efficient exact attention with io-awareness.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Flashattention: Fast and memory-efficient exact attention with io-awareness

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:02.231331Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.623094Z digest=sha256:11939eef1336fe4b515a25aea663030ef58c06393cdba3ba0e1e8a690c4b79b0

Observation 7a7d3319-d2a7-4104-923a-d3cd56bea5ae · outbound

This paper cites P., Caron, M., Geirhos, R., Alabdulmohsin, I., et al.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers P., Caron, M., Geirhos, R., Alabdulmohsin, I., et al

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:02.080751Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.726126Z digest=sha256:33e8d02057e6b5c4e9cff3944b6f6f633e45dc04f068d92bbff6a142c8a051d1

Observation 2a879326-452a-46b1-9d0b-5353a0dc34c8 · outbound

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

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Imagenet: A large-scale hierarchical image database

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:45.802701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:45.802701Z digest=sha256:103edc85469e0e3f190a828abaab4fb8b19fe78f71389d74704ab09c855dcb7f

Observation e39f7842-c5c1-47c9-8bd3-60cc395b71d3 · outbound

This paper cites Acnet: Strengthening the kernel skeletons for powerful cnn via asymmetric convolution blocks.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Acnet: Strengthening the kernel skeletons for powerful cnn via asymmetric convolution blocks

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:01.897203Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.874654Z digest=sha256:500fc1076eba244c40bb0b1623a18677acc61b5c9b61b1de283f6bfaf0c0b2e5

Observation 6fc45d22-443e-480c-972a-8c2472add66c · outbound

This paper cites Diverse branch block: Building a convolution as an inception-like unit.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Diverse branch block: Building a convolution as an inception-like unit

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:01.764041Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.944759Z digest=sha256:42245456cfa6d97d46abac4b5b84fd7ab9dba188a6f6ef0b01508b014d378b7e

Observation c6d97798-378c-41d3-af77-528396fbcab9 · outbound

This paper cites Repvgg: Making vgg-style convnets great again.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Repvgg: Making vgg-style convnets great again

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:01.636099Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:45.994253Z digest=sha256:ce10bee492aab19d6278796b896ca2b64ea2a2f75d0d672e98fe3bac9e7b985a

Observation 586e35d0-a13d-4d6c-a29c-2faa2603e593 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers An image is worth 16x16 words: Transformers for image recognition at scale

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:46.050615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:46.050615Z digest=sha256:6adea2f8e9736427dfdd9631ae1913d692636d2b3f06b92d222b4563a21b90dd

Observation 107d7008-27b5-4789-88dd-31151b5be27d · outbound

This paper cites A., Jafari, F.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers A., Jafari, F

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:01.464000Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:46.116886Z digest=sha256:33241e6d648685dd154a5edb00a5eb0c02b1cf4357e10cb0068d3c289605d8d4

Observation 7e416a1f-1cb1-42d6-bbe5-5f15dfc842d2 · outbound

This paper cites Levit: a vision transformer in convnet's clothing for faster inference.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Levit: a vision transformer in convnet's clothing for faster inference

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:01.280521Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:46.215126Z digest=sha256:ce930e2c8cb3e6fe7bee45dd1d2b455c2bcd386c38d2f6531aa7956d5f563e27

Observation 276eee30-f9b5-47d9-8816-6668376fc167 · outbound

This paper cites Slab: Efficient transformers with simplified linear attention and progressive re-parameterized batch normalization.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Slab: Efficient transformers with simplified linear attention and progressive re-parameterized batch normalization

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:01.107677Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:46.318270Z digest=sha256:eb06004a23eabc5bc77285d67ce82cdcf4a31a2654bb1281a858ec2afd52b1d2

Observation e41b8e09-14fe-4d83-9d2c-4905aabd6f7b · outbound

This paper cites M., and Salzmann, M.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers M., and Salzmann, M

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:00.956968Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:46.444120Z digest=sha256:53185d289db1b795d49f2f33fd91c4d78a83eda6838d14f0ed6e5eda6c962176

Observation 58314a25-db5f-497b-8631-a5f4851ebb12 · outbound

This paper cites Learning efficient vision transformers via fine-grained manifold distillation.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Learning efficient vision transformers via fine-grained manifold distillation

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:00.819100Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:46.546244Z digest=sha256:c71c143f65e769cc8e4f8f8d9e6ad45f846dfcf24d80ac94c3e108d8afa8557e

Observation 001aa655-7d4d-4920-8ff9-396881e675f7 · outbound

This paper cites Mask r-cnn.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Mask r-cnn

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:00.630452Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:46.637831Z digest=sha256:59dd3008ce74afc2df584a120d2179f0958417d432ebcb7da633d72f6a2ae40a

Observation 80b4a332-4a87-44bd-b65b-bff09d8dd2e1 · outbound

This paper cites and Zhou, J.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers and Zhou, J

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:00.516499Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:46.806769Z digest=sha256:5d4c93709957b731c232b7e05888604067d03e7c03fb76e2910cfe0569d3249d

Observation 8b6147a6-db25-4f52-8ceb-9c1ff9fdd652 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Gaussian Error Linear Units (GELUs)

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:46.959811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:46.959811Z digest=sha256:28b2bce2304e84b28d76b04f765b71c529e3e691520200fbeaaa217e333ae085

Observation 8be553f8-3dc9-4720-858c-ad1d51358fc3 · outbound

This paper cites and Szegedy, C.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers and Szegedy, C

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:47.077445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:47.077445Z digest=sha256:802319d1ff87b9c291c170c2b8265c0e768f3b3b0b68b8458fc44071bc673171

Observation 5871e259-b89f-4649-a3d0-58f4943f4c90 · outbound

This paper cites All tokens matter: Token labeling for training better vision transformers.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers All tokens matter: Token labeling for training better vision transformers

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:00.302547Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:47.246475Z digest=sha256:fc49c98e65d0040759260984f1f7f65fb20171d818be17536c58586ccf912a1a

Observation 583a81f1-72c5-4dc6-97f8-18d27408e5b2 · outbound

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

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Token fusion: Bridging the gap between token pruning and token merging

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:00.211461Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:47.376598Z digest=sha256:5e7722a686f38053a83ac325a304e7d0589cca5fe7e8a467b43754e79d0ba6dc

Observation 31521059-d2e2-4c46-ada8-d1204e846bf3 · outbound

This paper cites C., Lo, W.-Y., et al.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers C., Lo, W.-Y., et al

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:47.552353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:47.552353Z digest=sha256:3696fc2bf925c929bc2c5c1f63b0c95298ebf12b6c134cad6ab25717b8867490

Observation 68faef66-af34-4bd9-acdb-f08dd434f0d5 · outbound

This paper cites Spvit: Enabling faster vision transformers via latency-aware soft token pruning.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Spvit: Enabling faster vision transformers via latency-aware soft token pruning

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:00.057259Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:47.690572Z digest=sha256:0da666b2b26243ec909bb856cb54b50d08ef936262b0cae003ec86f73ca2342f

Observation 84aa4104-373a-44a9-adc9-22026226a860 · outbound

This paper cites Peeling the onion: Hierarchical reduction of data redundancy for efficient vision transformer training.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Peeling the onion: Hierarchical reduction of data redundancy for efficient vision transformer training

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:59.834091Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:47.838915Z digest=sha256:9048148ec6a6a5c220d8edc636fe38a7f3cae42e63e9c3379a8766665a50daeb

Observation 21e8091d-0c9c-4465-aace-e3674f08da32 · outbound

This paper cites Layer Normalization.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Layer Normalization

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:47.977714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:47.977714Z digest=sha256:2c78a74bd1bf8de14c5394c095f4182b38c168fb0be179c822eab0710aee7359

Observation 2fb3272e-e312-49e2-9f84-cb9a7248ed6e · outbound

This paper cites Efficientformer: Vision transformers at mobilenet speed.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Efficientformer: Vision transformers at mobilenet speed

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:59.694685Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:48.111751Z digest=sha256:1218e479a7c925e4e21fcdc9d9d76318bc35d8f005202e15fcfb84dd3b35d2ff

Observation ad50d6bf-0615-4e30-b282-3cbb5624d3f5 · outbound

This paper cites Evit: Expediting vision transformers via token reorganizations.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Evit: Expediting vision transformers via token reorganizations

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:59.553606Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:48.201879Z digest=sha256:a9b4f1f4e10a9440ae93c81b636a7268429c9f59d5ce16b27c549c07f99ef054

Observation adf8f4e0-881b-4bc0-ac86-28cfd651d7ec · outbound

This paper cites an unresolved cited work.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Unresolved cited work

Reference 34

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no resolver link, observed 2026-08-07T13:27:48.327152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:48.327152Z digest=sha256:e7a081fddee5d16c8a758362ec950eef498ff1fcae4812dc96e2d68600f06ca7

Observation c81e5e95-9bde-4820-95af-385fd44a0a0d · outbound

This paper cites Focal loss for dense object detection.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Focal loss for dense object detection

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:59.338012Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:48.446370Z digest=sha256:3ad2ac6449e0ba3c44d25d3f72ff79236135b2a80b27d31baef991ac5c12008a

Observation 93879e39-691f-432c-a73d-8ec681ce0156 · outbound

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

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Swin transformer: Hierarchical vision transformer using shifted windows

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:48.547213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:48.547213Z digest=sha256:7b2d662519c920aa48a3dc409108f497b3a97cb64e14014d33117d7efcbbe0ea

Observation 10865df5-a497-4bb3-91fa-978eeb2854ed · outbound

This paper cites Swin transformer v2: Scaling up capacity and resolution.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Swin transformer v2: Scaling up capacity and resolution

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:59.197755Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:48.698722Z digest=sha256:db13b6abd0c06b0d24090e06a372b9657cc0feb8d5b9214d80797e8d80bd5420

Observation 9c7bac21-6077-4886-ac1e-535ae15e0c25 · outbound

This paper cites and Hutter, F.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers and Hutter, F

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:59.022633Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:48.803361Z digest=sha256:d711ac9c21f88fd9f7b00782be48a50358845da18d5c8058ff39f12ae119e68b

Observation ea23cbc8-37b1-4916-820c-11a6e864b438 · outbound

This paper cites Shufflenet v2: Practical guidelines for efficient cnn architecture design.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Shufflenet v2: Practical guidelines for efficient cnn architecture design

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:58.824559Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:48.898547Z digest=sha256:3ef514c3cd1f7fec5e4f0da3c7d082679f07c970c2069bd594f3d6af46700452

Observation b6617482-8fdb-4917-a0aa-ba957599c1fa · outbound

This paper cites W., Anwer, R.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers W., Anwer, R

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:58.648782Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:48.984726Z digest=sha256:d607b1f20c53d548248a0ed90de3fefef73670bafde5cd772bbd18ceb169b94e

Observation 67f50afa-18df-4970-ad0d-5896990e517d · outbound

This paper cites R., Ranjan, A., Prabhu, A., Rastegari, M., and Tuzel, O.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers R., Ranjan, A., Prabhu, A., Rastegari, M., and Tuzel, O

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:58.396689Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:49.103051Z digest=sha256:b201a8baf08245c5e51a4e8632c66f636cd9333bf0517b9481b8bdad621a98ee

Observation 762ebb6e-a574-4ae1-949a-d2d4967fbdf5 · outbound

This paper cites and Rastegari, M.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers and Rastegari, M

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:58.174781Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:49.262507Z digest=sha256:2a2c7e6b8a7adac02b12ded0aae1693a3b1cfb65c90b19d7fd7efdadcb6a595a

Observation a08e2317-556b-433d-b4ad-0f93a07ecdb3 · outbound

This paper cites Separable Self-attention for Mobile Vision Transformers.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Separable Self-attention for Mobile Vision Transformers

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:49.390514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:49.390514Z digest=sha256:6161f4a367787b473591d47e2e52f3518b104f91ca4824b60de6c5477500b1ce

Observation d3ace4f7-c42a-45be-b18d-3aff0346496e · outbound

This paper cites Adavit: Adaptive vision transformers for efficient image recognition.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Adavit: Adaptive vision transformers for efficient image recognition

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:58.058235Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:49.489537Z digest=sha256:10c457cc4b777003def883ea2463dad2b32497215c06597690ff4a48a025e4d2

Observation ecb10f29-70bd-434d-b93c-a7a2524a82bc · outbound

This paper cites Language models are unsupervised multitask learners.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Language models are unsupervised multitask learners

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:49.576398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:49.576398Z digest=sha256:ff4fbba292d0b5444e0012d755a8698b76f096fe3e4cc5a0932659a5404c0b82

Observation 9c0918c6-d211-48a6-88f9-1737db1fa045 · outbound

This paper cites W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:49.667378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:49.667378Z digest=sha256:8369d360127b23117cecb841d0596a0ba9bbb9196cd7af4fb1eb98d8efa85c0c

Observation cef82201-63f8-4b26-a072-5b84f5c0fac0 · outbound

This paper cites Dynamicvit: Efficient vision transformers with dynamic token sparsification.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Dynamicvit: Efficient vision transformers with dynamic token sparsification

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:57.855534Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:49.805577Z digest=sha256:e427d4dd3e2c7744ae4acc9ddae6b57b06aacafb5c31cfa084d0ef5fef83727d

Observation 51aa05e4-0e6f-46bd-9a94-95740ae5c9fe · outbound

This paper cites Tokenlearner: Adaptive space-time tokenization for videos.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Tokenlearner: Adaptive space-time tokenization for videos

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:57.668346Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:49.915029Z digest=sha256:e935edd9bc07bc9cd2f9a6f411e3c3b5f1fcd2bd17e358b3ba98a4c81f6555ef

Observation 7ce0a290-1548-4e63-8aaf-be3e24e30ec1 · outbound

This paper cites Laion-400m: Open dataset of clip-filtered 400 million image-text pairs.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Laion-400m: Open dataset of clip-filtered 400 million image-text pairs

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:57.517771Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:50.020909Z digest=sha256:57eaac0a3e68c35e29a05419cfa4cf00d0a0dff03519cfd6cea765dd16c101c9

Observation 44543590-2e41-4d79-af94-b4121503f056 · outbound

This paper cites an unresolved cited work.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:27:57.313663Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:50.148153Z digest=sha256:c257c23683912c6ee24107e46594445eb2068641b3f45ed67f3dd96b1070ce02

Observation 47baca31-c13a-46fd-a72e-77c254869a79 · outbound

This paper cites Boosting vanilla lightweight vision transformers via re-parameterization.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Boosting vanilla lightweight vision transformers via re-parameterization

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:57.100436Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:50.292668Z digest=sha256:dd112fb6f54281922747fdf9e0042f2b57f978a7139124c1327a8f2143316008

Observation c7e0cc52-2aeb-4d18-8508-c54c23b93fd2 · outbound

This paper cites Patch slimming for efficient vision transformers.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Patch slimming for efficient vision transformers

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:56.899339Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:50.382882Z digest=sha256:90395940a381768cb8f065e39c3237fa059df3ed04956118974aa178b3e947e0

Observation ac2fefad-a2ef-4db3-9f13-51155ba56c63 · outbound

This paper cites O., Houlsby, N., Kolesnikov, A., Beyer, L., Zhai, X., Unterthiner, T., Yung, J., Steiner, A., Keysers, D., Uszkoreit, J., et al.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers O., Houlsby, N., Kolesnikov, A., Beyer, L., Zhai, X., Unterthiner, T., Yung, J., Steiner, A., Keysers, D., Uszkoreit, J., et al

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:50.487356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:50.487356Z digest=sha256:c32d826c09bbff3f38f2dcfa00ca019546a414d544d151170317d2906f147097

Observation 54b9af9f-ecc3-4fdf-b9f3-0de8c149e7bd · outbound

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

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Training data-efficient image transformers & distillation through attention

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:50.589425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:27:50.589425Z digest=sha256:01ac39d760277a251ea35ad13c6eaf667f6c989085c6aa8b6cf4827a45fd7208

Observation 56638012-8504-442d-b086-80653ce9b30a · outbound

This paper cites an unresolved cited work.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:27:56.717237Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:50.682653Z digest=sha256:83558c72056c9028c12f766e13e5249f02f0e637b28a78811e269163df0307b6

Observation ed1f0c29-1b8d-42d9-a0dd-ba745c2890ef · outbound

This paper cites an unresolved cited work.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:27:56.579863Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:50.786098Z digest=sha256:4cab270e8f0de0c73d6e0cecacfcd42ee659bd37eccf8ec81c97e3da0698873d

Observation fad1a498-d8ac-43bc-a93a-65ece657a40d · outbound

This paper cites an unresolved cited work.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:27:56.457303Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:50.930776Z digest=sha256:fc4855c2e21cff40590ee33bf07183ed14bf7731bfcf53e53428be45c52e8312

Observation 578024ba-7d68-4a1e-885c-6a10efcfbbe3 · outbound

This paper cites Repvit: Revisiting mobile cnn from vit perspective.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Repvit: Revisiting mobile cnn from vit perspective

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:56.374338Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:51.030146Z digest=sha256:dacfa34d0aedfa33163ec6645a5e3e48d8a669d30f2e731e68a9f0246968719e

Observation c337ad37-fbbc-487e-9174-ae239a0cbacf · outbound

This paper cites Tinyvit: Fast pretraining distillation for small vision transformers.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Tinyvit: Fast pretraining distillation for small vision transformers

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:56.290161Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:51.145314Z digest=sha256:f7d176bd8937d872950e9d9b399fd7f221860b62e861c61a5dd2fe157cc63ce5

Observation ad20b943-0dc2-46bc-9cd0-d7b74bd3ba8d · outbound

This paper cites Unified perceptual parsing for scene understanding.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Unified perceptual parsing for scene understanding

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:56.190669Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:51.252746Z digest=sha256:38006c937362736d8c5dc87037267f9325dd9d55d535740cb85e4b1ccc9442d4

Observation 62a26267-f6b7-4464-bd8d-a0228ad2db9a · outbound

This paper cites Lpvit: Low-power semi-structured pruning for vision transformers.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Lpvit: Low-power semi-structured pruning for vision transformers

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:56.084181Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:51.371560Z digest=sha256:9ce9e2d1ce4e9fa4c705044b552e075dbd013445e4c0ca14552bc76bf8640aa2

Observation fcba0f38-2ad7-4226-8eaf-b09535648e71 · outbound

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

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers No token left behind: Efficient vision transformer via dynamic token idling

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:55.967534Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:51.472356Z digest=sha256:3b1b0ad3ecde230402e9b228a4481161749d3fef7c4283ae92ab5ee4221c7bc6

Observation 992f239b-c57b-4534-a46f-5282e8b0f7bf · outbound

This paper cites Gtp-vit: Efficient vision transformers via graph-based token propagation.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Gtp-vit: Efficient vision transformers via graph-based token propagation

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:55.889411Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:51.595649Z digest=sha256:e70f2eb2beea2210f35b096f72d236583181b55d3dd47ac25189c6303a9bc0eb

Observation 20cd2ca3-0c6d-45fa-bd68-31c7d96c778b · outbound

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

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Evo-vit: Slow-fast token evolution for dynamic vision transformer

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:55.787076Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:51.738104Z digest=sha256:5151edaa6871be5dc64084bb2b0ef4c98f544b05fe395ed76c7920ba03113652

Observation 7f95e591-944e-453d-88d7-d918a7186e96 · outbound

This paper cites Leveraging batch normalization for vision transformers.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Leveraging batch normalization for vision transformers

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:55.594717Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:51.870741Z digest=sha256:c05cfc9bbc3e6a4a940a131994ca3cf40c0a1ed28eec6ea103a724d8a9a66770

Observation 142e6176-d48b-4ab0-82de-ae8065d4b708 · outbound

This paper cites Large batch optimization for deep learning: Training bert in 76 minutes.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Large batch optimization for deep learning: Training bert in 76 minutes

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:55.477732Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:51.959625Z digest=sha256:5c33bb701f21e0ffe2801432b57e5d0550189ab9203aa5ca6063f9098dde29d4

Observation b78f0dae-a69b-4b29-8f3e-b797d3f6343a · outbound

This paper cites Width & depth pruning for vision transformers.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Width & depth pruning for vision transformers

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:55.384890Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:52.046635Z digest=sha256:7ca47d51d569e258e33eef22dcac2384f5c1b019490185c25b8c8232d855bc6f

Observation 305e0de4-e5f0-4e51-a0a7-1ac43ff86ced · outbound

This paper cites and Xiang, W.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers and Xiang, W

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:55.179975Z

Source-reported events for the cited work

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

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Observation 3ac8b611-267f-4a40-a11e-ee862bb4c0c6 · outbound

This paper cites Unified visual transformer compression.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Unified visual transformer compression

Reference 69

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Source-reported events for the cited work

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

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Observation 8b4d8ded-bdd4-42b6-9a3e-060e100cecf5 · outbound

This paper cites Metaformer is actually what you need for vision.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Metaformer is actually what you need for vision

Reference 70

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 259ca026-1a4e-436c-bc1d-a65ece044b40 · outbound

This paper cites Dense vision transformer compression with few samples.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Dense vision transformer compression with few samples

Reference 71

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 43b9cfba-efb7-41c5-b52c-8bebd30db120 · outbound

This paper cites Rethinking mobile block for efficient attention-based models.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Rethinking mobile block for efficient attention-based models

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:54.076400Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:52.594816Z digest=sha256:f279c8889847ee19de22ed489d72721deb3a6f8d90e478121beec08eee8badd9

Observation 5c58d379-8672-4e26-93fd-3cf9774fa3fa · outbound

This paper cites Scene parsing through ade20k dataset.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Scene parsing through ade20k dataset

Reference 73

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 3591acdd-0f44-4d43-8dc3-46089805a773 · outbound

This paper cites Structural reparameterization lightweight network for video action recognition.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Structural reparameterization lightweight network for video action recognition

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:53.577698Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T13:27:52.872038Z digest=sha256:0b6cf6686fd28a3eecf05c7ca83a600952797c06c11546e96de5882c8cbe5eb4

Observation 9ad4d017-621f-4db3-9757-9c69379ab265 · outbound

This paper cites Self-slimmed vision transformer.

RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers Self-slimmed vision transformer

Reference 75

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Pith citing papers

Observation 7959b44c-82ad-4bc6-9a81-2769acef33da · inbound

TRACE: Thermal Recognition Attentive-Framework for CO2 Emissions from Livestock cites this paper.

TRACE: Thermal Recognition Attentive-Framework for CO2 Emissions from Livestock RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-14T23:23:15.961256Z

Source-reported events for the cited work

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

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Observation 8ba57d15-e1cb-49b7-97bb-3520375753b0 · inbound

DeVIT: Low-Power Vision Transformer Acceleration Using Delta Computation cites this paper.

DeVIT: Low-Power Vision Transformer Acceleration Using Delta Computation RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers

Reference 22

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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