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Paper Citation Record · LEDGER

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

As of 8 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.005435Z digest=sha256:0aa36978ac9c5c436766cd8dfd4fd676f0ac4f16dfe0a287b7b89517789fd0a7

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.078005Z digest=sha256:94329092657ba254e5fc859b619ddcf4d2a50f25364d238113b17bed76f4f35a

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.148509Z digest=sha256:76f0f9d202d941ed63dd0837a554ac58f50eb384859816a2db997cc637f52843

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:a930b99b491d7122b8f851f7781f043203ec957db3885eab0179ebd5a58c9cb7

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=sha256:2d76560d063954bc32059e1d801ede1ba2de6f5980b37c68e5443bd029c0b4d4

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.357089Z digest=sha256:3e20a6409741c5f773fe05e99eb4903b3c3a2a2082e6d626cc5d49a0235bf13c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.439229Z digest=sha256:65359440ea33b50af25faa1b8ff2ed1fd794956e6cc367604a5eaf9753ce2cb6

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.505134Z digest=sha256:e1742fac031a24afd73d2db3d36d8c2b73db4b3cec2f798e753067cf77367209

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.556904Z digest=sha256:461f1092ea86d4025921126ed2844e9eef7190905be50789722762588f1403a0

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.623094Z digest=sha256:039c7cdabea6eb2c5925ca2da85356c8b6e4cd163fbd8fca536b99eac06d0267

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.726126Z digest=sha256:58f6d44d11b922b2ef6f205f34b4441b70e8accda638fc91b68a0c983f387926

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=sha256:1fc3cb170da81615955501e5412e0415ca131c8c1e345b2292e825bfada366b4

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.874654Z digest=sha256:bf7a5d98ba0b4a06f77bc259d78956597ebdbc09f05b33be8a26fd8aa991bde5

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.944759Z digest=sha256:bced3c5ec6a9cb935090bd5f60420f93da35b32e717e42639b7e690d0a3eec5e

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:45.994253Z digest=sha256:9d581219c4635879b26c737087ed6c3367dab52a155d66c60c02b860b21bd05b

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=sha256:7587676a469c9ba1d075de27cbc426cea438474d6cdfd1fe95a3a498bff7df09

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:46.116886Z digest=sha256:62884a15970da6989e50ebcb2a5a78b20faeec2e2de09d35c21e4abb2d4a6254

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:46.215126Z digest=sha256:9ba9430184bdf2ee73e56843f812c691f9dcd5fbd2a2c1ef3aa9354e77c69342

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:46.318270Z digest=sha256:b52d273879a9233d336233d0cf64c101f2c198838a1d5841ccc3003b193e25ee

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:46.444120Z digest=sha256:3023725bea09aa8aeb4d056bd888285e9ec6709ce27539e4b33907456007be2a

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:46.546244Z digest=sha256:f6547bfe1559afc7b226b207b01ef723170638fcb5bfea2f3e5b9d005843e9c7

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:46.637831Z digest=sha256:ce13f0de500b1058b4340aca549375b5f5b2f3db5342db0b42a2312834cbd620

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:46.806769Z digest=sha256:baaca32f1549d7837c8b4087b773f89f5c99baf0a0bf0311d0cf87f2841da98f

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:d4b25e32bbfc61d6d897a7817a819ac60698642cb9aee0400265685cf3cb6495

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=sha256:9609f318c6c0e3cb5182601238ccab3af212669bfa913293f3b5b741f8f31317

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:47.246475Z digest=sha256:28f643ab4a5bf7d37df4a548e17969203bece5c1a561cb6ca9b4d49655e50095

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:47.376598Z digest=sha256:3b1216adf026f77b7feb56536f357e1acfd4b90b477151332932be33db4a7e15

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=sha256:80cc86a826bd3629d5681dc546881ca35723c48c486d674580f6171bcc3405fd

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:47.690572Z digest=sha256:faffe0e189f02f30af967444cb94fff35ee63007094ee11b2c7b029bc64f8763

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:47.838915Z digest=sha256:efdf3934efa4aa52aaf2b74834c26cd1f7aa4843ce2873f5c6b0c4c44e1c252c

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:fd7ecc04c03c3c96e6705a2e5bc7bca1994805920f30078de0b84caa19b3bfc4

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:48.111751Z digest=sha256:e4b992360ab6fe9824aecd77e8a2a2891165cd5d62137916a4f105a41070e60e

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:48.201879Z digest=sha256:a9a21b8798cd6e1e8b9fda70373b47e49db8e8faa6b0336b579f601bdd2922b2

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

Resolution
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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=sha256:8e96fb3024c559cc368db7afa6ee52edfd0f84300b146aa016fd188039eba2fc

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:48.446370Z digest=sha256:8fd1be7c17c650d26014f04ecf4b7e7fd507a930c9e9d4ef2141525d7263e49c

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=sha256:8292e3572f9620df0fa06db7dd763c03bd2073fd5e1efcb9c77d5b7131040735

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:48.698722Z digest=sha256:df8c5b1b1a36daee2755111f984e5710b4d0e170eaba6896e4fe7bafde5b11f5

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:48.803361Z digest=sha256:7037afe10b18b92a82f1ecec36198631a5874302917fc6c2b01be98529524661

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:48.898547Z digest=sha256:667bd9242a6439425338af2dac3e2aa123b53e078952dc2a83b98c634d1c12f4

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:48.984726Z digest=sha256:851a5a962225e75ac3ddf983cbb16f9f0313a6e57ffbd89442b432513dc91636

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:49.103051Z digest=sha256:3e3cb3b12e6e46e6c94a7c101efbcf0167c7f4d422dd37252611840f31958716

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:49.262507Z digest=sha256:368f2bf16bd685ee6832ebd39ec90bbf1b50089417362996a85ebbfbd87906aa

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=sha256:06d94669819dacb99d012681bfcbf4be7bc9b8eecbe221bd109f3e7fa062718f

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:49.489537Z digest=sha256:f824c3e3f7928f39d8c06ca699c99d168e79c7106bf12bbc50fb82872ccd9fc8

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=sha256:7a7830611dc4582f7e60ebb320222b22940d2774c6e6cfb53dd2b713954b4afb

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=sha256:08ef299231cec14782e3bee6c4b9d60c5c65141bf803f484fdbaa99c70e641d6

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:49.805577Z digest=sha256:3ec013f10cb3d73f389f46dae04d50e7eeee713f0a1bcc7ea6f64cd7cd335cbb

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:49.915029Z digest=sha256:8f8ef39b7e6573f15afac9bbfa35cc270db69ea31b2fac9c2ee85a8b3d5347ed

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:50.020909Z digest=sha256:1678c4fc3efc90758ce247a6b48ead094f6ff387cbb9c91ebb2f981fc76c548c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:50.148153Z digest=sha256:903cfb0156ac8c5f155fe9c356f9b7dcd6384bafb0d2f2a423970e67eb721394

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:50.292668Z digest=sha256:bd780f5116a79d4d76a6b0f93cf7ea7f26cceca3e308921b655853f866102424

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:50.382882Z digest=sha256:cbb1ed6ede13278a66ca13194e11ab5ce0dedb4ae092389c8cdce779fe268567

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=sha256:88f2f76857c1a78858bbe84fdb19ff5f53d794039b39aee95b1ecc9c6cc67a6e

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=sha256:4769e5f36d3bfa58e3b68d04bcd1bc6214386c0b26363e89696868fa306e80d7

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:50.682653Z digest=sha256:0e842703472347bfced814ba3bfd09903938abcd1a7ad2c9376013bf42af8d30

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:50.786098Z digest=sha256:c96fd8701156a37a224e416c17723421083da37f3c59196774f21b45e53288bc

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:50.930776Z digest=sha256:3b5c317dcacf8e6bcb5f6e9c854cf21fd82958592bfbdcf9fbf51447ebd82626

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:51.030146Z digest=sha256:44d7d9f603c820cad141f9ee65269fa069863886946749b1bf2aa3e204685a86

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:51.145314Z digest=sha256:196311f7ce4d06fce45932e7eed3cc923c5bba17333e91f31a60f5ff96b41f6d

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:51.252746Z digest=sha256:30ad1452fd5a7d62386e7b9a22598b2d497b858a6c74d27abb14b81d7db101b6

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:51.371560Z digest=sha256:e481339b134c625e63bf20f112ef4a390787bdcf2a65c1bd6b9975a5ccf6c74b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:51.472356Z digest=sha256:0c5efd4b902b233599d9261feb36cd191c70a027d41ba4984e51ecc0721b1edb

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:51.595649Z digest=sha256:6dc747d665965291f06aa897f0bf37b9bb62fd0aac67e4284beff83892d269e6

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:51.738104Z digest=sha256:01d771984091fecc33949f02c920b7307e0ccf95e68192fc450c86b1ab33e5e7

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:51.870741Z digest=sha256:a83956c665fccaab6dd48ce78c3a7a709face304196f2a5cbd741f8f2f22d634

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:51.959625Z digest=sha256:73cc10f567364582a864516439a6b3fb1eb139ee3b94939939430b946e46818e

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:52.046635Z digest=sha256:1a85c586d0f25f4cdb719b3a965cf3adb209c86f2226df11787bb494b4e0fde3

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:52.195065Z digest=sha256:a9fe399194e761ef894e3f2c4d42fb563fec5b934d96f53695d4bcd9b538be85

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:27:54.959345Z

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=arxiv_source observed=2026-08-07T13:27:52.277117Z digest=sha256:9c64198974f5193c8cec5d9efdd44ea1c33b8c597691b95ad617cf6c38bace3f

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
raw_fallback, observed 2026-08-07T13:27:54.749064Z

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=arxiv_source observed=2026-08-07T13:27:52.411959Z digest=sha256:275f843b7eb991f9aaeee850d381d54942d5b64a5e8bf279f575bcdba5ce9b74

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
raw_fallback, observed 2026-08-07T13:27:54.412604Z

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=arxiv_source observed=2026-08-07T13:27:52.508299Z digest=sha256:1b51c44c5e3ea36c31a3e958d3df0731f1e2755ce49ad5a93d9be85e07c8e27b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:52.594816Z digest=sha256:af3914286cc67c9637506e69079825262162cb8b7a3738aa65cf4355c8d4fefe

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
raw_fallback, observed 2026-08-07T13:27:53.796137Z

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=arxiv_source observed=2026-08-07T13:27:52.716081Z digest=sha256:4563a6ea8d34d301e0719281dec27019ff71aaecead604f4b00929e7aeeb40a5

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:27:52.872038Z digest=sha256:c70d0a9acf7b7033aaad5c85a0058909a61e4f3d6e1f29d656760d504ed6c16b

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
raw_fallback, observed 2026-08-07T13:27:53.313550Z

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=arxiv_source observed=2026-08-07T13:27:53.028375Z digest=sha256:5b64382fa99e4815c213225504b91fac97e127aa83ad9efbc382bec4771af744

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-14T23:19:53.767212Z digest=sha256:4269b78b2d8b095308d06be4f23e0006319708956431f2080175d1d2fcff1283

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
unresolved
no resolver link, observed 2026-08-06T00:24:55.763468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:24:55.763468Z digest=sha256:fd42eab5c2b00c0a71c37fc381e81079cdd00429f1a86605c8cf5e6068755151