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Paper Citation Record · LEDGER

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms

As of 8 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2508.01385.

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

pith.paper-citation-record.v1
2508.01385 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:44:19.945057Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

  • verified exact3
  • verified fuzzy21
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8191d702-a6df-4fc8-943e-b0f7eccb126c · outbound

This paper cites MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

Reference 1

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no resolver link, observed 2026-08-06T05:44:19.757686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.757686Z digest=sha256:e21fe38b2bc07c171afe15bb658cb2168dcb80e74507bcea64199cfdc0ab6712

Observation bc011898-f845-4824-a3a9-09eab2781542 · outbound

This paper cites Rethinking spatial dimensions of vision transformers.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Rethinking spatial dimensions of vision transformers

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.579127Z

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=2026-08-06T05:44:19.764004Z digest=sha256:935483b68922850903c5e916dde7064fc4d58783e8c66fb8aa76ee8bd7c3eb3e

Observation d6937360-5bf3-4f74-999c-d82347b21eca · outbound

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

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Mobile-former: Bridging mobilenet and transformer

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.564825Z

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=2026-08-06T05:44:19.768993Z digest=sha256:2138ca2c55514e36c2af99b87591f4aa17dd1ce7a4a071f0aa81f7173bfec264

Observation fd038ff7-c513-4206-aead-04106148c40f · outbound

This paper cites Efficientformer: Vision transformers at mobilenet speed.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Efficientformer: Vision transformers at mobilenet speed

Reference 4

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no resolver link, observed 2026-08-06T05:44:19.774169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.774169Z digest=sha256:f647ae9da94c450b2125164f1341ceeba2ae8ca1040d93521abc886daa9617ce

Observation 3799f2ca-9ad8-402d-aed0-e1626e0b9d6d · outbound

This paper cites Cvt: Introducing convolutions to vision transformers.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Cvt: Introducing convolutions to vision transformers

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.540477Z

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=2026-08-06T05:44:19.778978Z digest=sha256:a6c6cbeddeda3c9fd4c2083e280e2b06c7b7a4a7f1bc80033e77d12693061eb7

Observation 43973908-3670-483a-aa6a-24b75984db3a · outbound

This paper cites TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?

Reference 6

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no resolver link, observed 2026-08-06T05:44:19.783785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.783785Z digest=sha256:c4b2627408730ac1bab4ded523634328f37c94d5c54ca81912556c5f94e3be20

Observation c110bec4-48b1-4d23-8dca-5b7ed471d1e5 · outbound

This paper cites Edgevits: Competing light-weight cnns on mobile devices with vision transformers.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Edgevits: Competing light-weight cnns on mobile devices with vision transformers

Reference 7

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raw_fallback, observed 2026-08-06T05:44:20.525745Z

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=2026-08-06T05:44:19.789439Z digest=sha256:2a27fcdf990a2dbe91197f6e6bc59af8afaa8ee655c689b525c1b644141b2cf2

Observation 011a6116-2d50-472a-86b8-0e3bfc3aad85 · outbound

This paper cites Hiri-vit: Scaling vision transformer with high resolution inputs.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Hiri-vit: Scaling vision transformer with high resolution inputs

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.510036Z

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=2026-08-06T05:44:19.794084Z digest=sha256:10dd3acfccf873f38843437dd6f6c639ade5d812011d527ef10a128561af0936

Observation 99140d0c-e9f3-476f-b9c4-df0c9e78fe3f · outbound

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

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Levit: a vision transformer in convnet's clothing for faster inference

Reference 9

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raw_fallback, observed 2026-08-06T05:44:20.495380Z

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=2026-08-06T05:44:19.798724Z digest=sha256:168df38d02e6c64a473c1e6a647bddea51890f7ee6794f7b077557ebda7de74b

Observation 89b77a0e-de23-4c6a-aba0-6764822cb82b · outbound

This paper cites You only need less attention at each stage in vision transformers.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms You only need less attention at each stage in vision transformers

Reference 10

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raw_fallback, observed 2026-08-06T05:44:20.478633Z

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=2026-08-06T05:44:19.803335Z digest=sha256:3ec44ab49492b5a13196eaa2a45c04885e21e18846c4eec694fafeea9156a7ad

Observation 220150ea-8be2-4c41-ad5e-e18e019d7a0b · outbound

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

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Separable Self-attention for Mobile Vision Transformers

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.808852Z digest=sha256:474bb3790296379f63e2d7bba6c2037ae9e3cb46c6e0491e7a9516537df875b9

Observation 7daad04c-00c6-4ac8-82b8-1b84d17c6381 · outbound

This paper cites CAS-ViT: Convolutional Additive Self-attention Vision Transformers for Efficient Mobile Applications.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms CAS-ViT: Convolutional Additive Self-attention Vision Transformers for Efficient Mobile Applications

Reference 12

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verified exact
local_arxiv, observed 2026-08-06T05:44:20.157238Z

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=2026-08-06T05:44:19.814256Z digest=sha256:ddf67fd2e531e4e71727712e96951f2cb8582f14abbdf57187b6e5202d47e4f7

Observation a8eb2e59-bd86-4751-a2ac-5d8f4a54855e · outbound

This paper cites EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction

Reference 13

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no resolver link, observed 2026-08-06T05:44:19.819183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.819183Z digest=sha256:be7508bfb2eac5c303af919be970e4fe04a7bc7a234864cd6aad9a23661fc9e1

Observation 7531734d-8ff8-4434-9d67-5f8dc938b9f0 · outbound

This paper cites Lightweight Vision Transformer with Cross Feature Attention.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Lightweight Vision Transformer with Cross Feature Attention

Reference 14

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verified exact
local_arxiv, observed 2026-08-06T05:44:20.118621Z

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=2026-08-06T05:44:19.824159Z digest=sha256:e00920015fdf8624b12fc27728bb560080a42c3dff8195fbf18f2236d3d4f8a3

Observation 3483fb26-834e-4904-a20b-bba88b621651 · outbound

This paper cites FasterViT: Fast Vision Transformers with Hierarchical Attention.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms FasterViT: Fast Vision Transformers with Hierarchical Attention

Reference 15

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unresolved
no resolver link, observed 2026-08-06T05:44:19.829104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.829104Z digest=sha256:969ec0d3e78cbfaf27129a5d237ff4cbaa2d4666080c7105f9366670ac973ac5

Observation a475910d-9df1-4e7c-a841-a4cf4bd531fc · outbound

This paper cites P 2fevit: Plug-and-play cnn feature embedded hybrid vision transformer for remote sensing image classification.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms P 2fevit: Plug-and-play cnn feature embedded hybrid vision transformer for remote sensing image classification

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.462584Z

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=2026-08-06T05:44:19.834071Z digest=sha256:48042f1bf3ac9a82ef261c8384b8b0685560feb714b23fb3f569a656a514efdc

Observation a9675922-5263-4ea3-a3d7-32672b1e78b1 · outbound

This paper cites Restoring images in adverse weather conditions via histogram transformer.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Restoring images in adverse weather conditions via histogram transformer

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.447193Z

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=2026-08-06T05:44:19.838617Z digest=sha256:b7e3f479814001b9d8ad8f3d63d938865be3d7b68932b399967fdb9145df5a50

Observation 7e5f6150-ca55-45ba-ad25-a90f31f310df · outbound

This paper cites SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization

Reference 18

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no resolver link, observed 2026-08-06T05:44:19.842941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.842941Z digest=sha256:a865fc7be89267fdf64a50e6d5f7db7b8db11a35b7fd2bd3442bfa3597d947e2

Observation aa3eda7f-6342-4bd8-9ee7-0e01df890114 · outbound

This paper cites Agent attention: On the integration of softmax and linear attention.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Agent attention: On the integration of softmax and linear attention

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.432112Z

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=2026-08-06T05:44:19.847408Z digest=sha256:1076d991f4f128d52df52c2fba078bd596f369039b5a630c3a7b53df5da1ffb3

Observation 30193e2f-a482-4f26-a199-d88e2865fe4b · outbound

This paper cites Mobilenetv4: universal models for the mobile ecosystem.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Mobilenetv4: universal models for the mobile ecosystem

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.416877Z

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=2026-08-06T05:44:19.851946Z digest=sha256:cb36167e67f11343ce9106878ef1303e12a9d0c571d10994fa15666fcf62ccac

Observation 53799e33-102e-4479-8009-321ae5a8d4f8 · outbound

This paper cites GhostNetV3: Exploring the Training Strategies for Compact Models.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms GhostNetV3: Exploring the Training Strategies for Compact Models

Reference 21

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verified exact
local_arxiv, observed 2026-08-06T05:44:20.065811Z

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=2026-08-06T05:44:19.856190Z digest=sha256:44e5b23173d78a517e4e771dd91a189c6a19f1542f7edad8df2e8a2d335d961e

Observation 9619f540-ad33-4360-af0f-bac7641bca05 · outbound

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

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Repvit: Revisiting mobile cnn from vit perspective

Reference 22

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raw_fallback, observed 2026-08-06T05:44:20.401554Z

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=2026-08-06T05:44:19.860766Z digest=sha256:2fefae58f78834c9a7e31c1d071fbe42e49a44c5673715b2cbbcc5316cc44c2a

Observation da989c0f-9b92-4adf-9f2d-063ef7185fe5 · outbound

This paper cites Searching for mobilenetv3.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Searching for mobilenetv3

Reference 23

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no resolver link, observed 2026-08-06T05:44:19.865491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.865491Z digest=sha256:94a21030e667b74436ab7f683880d26ffef53f2dec9e04eb25cd30f4a73b0836

Observation c339e6c6-9c9b-4a5c-8365-49396c4be64c · outbound

This paper cites Patches Are All You Need?.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Patches Are All You Need?

Reference 24

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no resolver link, observed 2026-08-06T05:44:19.869609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.869609Z digest=sha256:36ab1294781f08cc5b829bc40fb49329ce94deddb755ef14aa114ba8a7e421e9

Observation eed4d6b5-eba5-4aef-b1b7-491ad8eb24dd · outbound

This paper cites Attention is all you need.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Attention is all you need

Reference 25

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no resolver link, observed 2026-08-06T05:44:19.874318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.874318Z digest=sha256:125fb98ff4b2f64fd82cf3d28cefda35c2916e605d3c58a1e9956e0d541a82e2

Observation 1aecca0a-650f-4c9e-9863-cff70e98f717 · outbound

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

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 26

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no resolver link, observed 2026-08-06T05:44:19.878573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.878573Z digest=sha256:a390435afc525973a8d38ae939b79ff5e5365acb2f8bad122dda5b52d1cbf04e

Observation aa042772-b615-4cda-b821-8add0a891022 · outbound

This paper cites Mlp-mixer: An all-mlp architecture for vision.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Mlp-mixer: An all-mlp architecture for vision

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.366209Z

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=2026-08-06T05:44:19.883017Z digest=sha256:e0bcb57ea5404ca940f8bad18fdc03d0cdedeaff0d3ba5013f63170140810f2d

Observation 92e29d65-a9c3-4c8a-82e6-0ca8dbe6455c · outbound

This paper cites Deep residual learning for image recognition.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Deep residual learning for image recognition

Reference 28

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no resolver link, observed 2026-08-06T05:44:19.887661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.887661Z digest=sha256:b33efc436390a615c34b22a202f8c6f1f18672d091e094dcfc6c243067d689fd

Observation c94871be-7c59-4075-b0db-9628c3612609 · outbound

This paper cites MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

Reference 29

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unresolved
no resolver link, observed 2026-08-06T05:44:19.893331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.893331Z digest=sha256:bd4ec4f01e7772d5c23e8ad135128e7c0d0f9092071bfaeae45ad988f06df62a

Observation e1d1c82e-6ac0-4653-8d5e-fbf4611e6432 · outbound

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

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Tinyvit: Fast pretraining distillation for small vision transformers

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.342407Z

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=2026-08-06T05:44:19.898187Z digest=sha256:f4b5aa416995f74fab4b4e3a657b83e76bb6bb349b7f66d15cbf26d8799d9ea0

Observation 924f76ec-b89b-407a-b924-672d5251b4ea · outbound

This paper cites Ghostnet: More features from cheap operations.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Ghostnet: More features from cheap operations

Reference 31

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no resolver link, observed 2026-08-06T05:44:19.902807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.902807Z digest=sha256:711dbbf4db3ea24d82a27a7cd2fca34c1d23d4b6ccc19996d02359e1ecabbcd9

Observation 019cee05-2ce2-4719-856f-59c91c87d2a7 · outbound

This paper cites Replacing softmax with ReLU in Vision Transformers.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Replacing softmax with ReLU in Vision Transformers

Reference 32

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no resolver link, observed 2026-08-06T05:44:19.907353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.907353Z digest=sha256:ccba88febcd7b5306e3fd43bbcdfa54ff93965f001ada0ee5a43708bd91a1c59

Observation 3dd92118-820f-4390-b504-aca5879ac459 · outbound

This paper cites YOLO series , 2024.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms YOLO series , 2024

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.317019Z

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=2026-08-06T05:44:19.912365Z digest=sha256:a952fe5e22d5fafb4eed73a342b61899979cde1b24851c6bfc678ca0935c3328

Observation 6c581df7-2a38-434b-b8d6-4107e566cfe3 · outbound

This paper cites Yolov9: Learning what you want to learn using programmable gradient information.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Yolov9: Learning what you want to learn using programmable gradient information

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.300693Z

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=2026-08-06T05:44:19.916916Z digest=sha256:5c5986ede970aa1034aea0d39aac0162475da34d17fff1a7f44f9caaf470e438

Observation 068d319c-4948-42aa-9235-e17034e9680e · outbound

This paper cites Yolov10: Real-time end-to-end object detection.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Yolov10: Real-time end-to-end object detection

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.282609Z

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=2026-08-06T05:44:19.921603Z digest=sha256:41916330899056c0bc2e4427ae3c0627cb237e12cf2b69eec1023cac449b96c6

Observation efe5a7ab-0ccb-4b6e-9817-424931821c67 · outbound

This paper cites YOLOv12: Attention-Centric Real-Time Object Detectors.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms YOLOv12: Attention-Centric Real-Time Object Detectors

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T05:44:19.926863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.926863Z digest=sha256:30adb55ea3e433aa3c4d4aabc1c3c825680eddbd7ea82104a75593581845040c

Observation cdb3d000-ec6b-4181-87bd-4a02c8eba6f7 · outbound

This paper cites Ghostnetv2: Enhance cheap operation with long-range attention.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Ghostnetv2: Enhance cheap operation with long-range attention

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.267886Z

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=2026-08-06T05:44:19.931744Z digest=sha256:100e22ea16f4e9b870afbe70be08f4db389f7d3ee7394b8ca1b8a9246f5c45e2

Observation 0c9369ab-6b9c-40b1-8a63-8e1d44a2d1f0 · outbound

This paper cites Run, don't walk: chasing higher flops for faster neural networks.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Run, don't walk: chasing higher flops for faster neural networks

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.252371Z

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=2026-08-06T05:44:19.936173Z digest=sha256:3da20c182413609353a87c93712ae1027698f7dc392dbdcd46204db4145e53fb

Observation 1c7b1fad-90ea-4b34-97ce-74fe18451337 · outbound

This paper cites Yolop: You only look once for panoptic driving perception.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms Yolop: You only look once for panoptic driving perception

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.237330Z

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=2026-08-06T05:44:19.940416Z digest=sha256:f9319d8ad463ca0eed4b38017df5436b1c1f18dad1b7e655b8ac270b292e4e61

Observation 9a59050c-24e0-496c-a1f3-8b6a95f080c8 · outbound

This paper cites You only look at once for real-time and generic multi-task.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms You only look at once for real-time and generic multi-task

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:44:20.221742Z

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=2026-08-06T05:44:19.945057Z digest=sha256:59615556fce892fcb68feb669959de51e227e7e3b652081814dfd966fff3bf77

Pith citing papers

No inbound Pith citation observations are available.