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Paper Citation Record · LEDGER

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms

As of 7 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 2026-08-07T06:34:17.273281+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=sha256:01f4b21dcc073a95a734d13b6177beb9dea545245b8a993a42804a9db7b199c2

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.764004Z digest=sha256:bca9eded944a875c463a46a9486c0205241ea4fa415b69789036d419218558f6

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 2026-08-07T06:34:17.273281+00:00.

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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:e82bf71f8bbe4d40331f99f406296fab8cce825bf4c04b724c1dbf3e3e6176b5

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.778978Z digest=sha256:0d4c32599417bfcf0f0d58ee6c32091c8371d8277c5c94a5ef1f00adc976b1a3

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:eaea657cd3d5fa39d1da5207cba1c454d5f3cd9d7457ad9daf95933ef58387e6

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.789439Z digest=sha256:8b6422d89d675ee9bd62dc8c6afa27b8c0a728eb713c09fb8c36dcf4954d6b4c

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.794084Z digest=sha256:bc782cd993be9af3fde1c25bb5bb4f95807e5784aa8132e7c87ccd6d2757f3b4

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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verified fuzzy
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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.798724Z digest=sha256:ba42b1b3d9b1fca6993d85a85ddd79244f9cb252f9437998cb73218561560266

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.803335Z digest=sha256:6560c2f30963966df44922cc46553dfa4e9bc46745e605250ba5bee2950c649d

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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no resolver link, observed 2026-08-06T05:44:19.808852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:44:19.808852Z digest=sha256:96ef9b18b82ff2263e2e0d8d8ecf6b8f92566e7747dcd915656a73e665a7ace9

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.814256Z digest=sha256:255ab64099c3a89dbdd93a43aa5cf9a689a7ddfc211ea2f68d15ea4a942d79b6

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:ddb556cba5af1682827a9851775d90e11e89a879212a0f5aa757452af918a456

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.824159Z digest=sha256:87aef25b582926c08f925d0d3a88ac16dbffa3ddd3a5d24a4f0b01467fe85353

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=sha256:3f881aec5f1d8ad811ecf80dfa77874a6eacf6dcbcd24a8368c2c1cd994eeb3a

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.834071Z digest=sha256:8ad553b02d180367452f4ef145a74e967e40c3ebdf59338ad281072b05aab3e7

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.838617Z digest=sha256:4038925bc156331cb8c68be6c77127af452a85bc12b05f36b5f83285a80e73cd

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=sha256:36f8b5a5d236a82af50502e8fc801200001d769569e8bc2669d20209f63d410b

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.847408Z digest=sha256:fe48371e546ee4532080c3e904fd3b86762b3c3e0bc3b49c63b211229f1e2648

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.851946Z digest=sha256:7ca9d589b651659a3acbedf64ac97ccef683ca9a212b0c03ec9b9677dcb3521e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.856190Z digest=sha256:795de42b981cb55e3532fffe89f7870fe3da21fda125416ffd8fd52dad47cd43

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.860766Z digest=sha256:26c79b8f7c2a9de180ca1221a41b57bffdd221c42121558e75fef2827867fedb

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=sha256:4c50332109e6e1f80136fa15bcfa9acb3f0ae6686563aef44edb0fb133e08f0f

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=sha256:3e8c368ba6b5906e6f5ad133f60a80fae0e97e46e06ba3a535e59960efd6c386

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:d2e6483e505bb90c26951839ba262d45f05bc12c64eedf2b8e9899c37252a090

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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unresolved
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:e935cc1346478e6a54539b6d896c144282a00a83d6129af6a58057aaf2cd4f52

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.883017Z digest=sha256:035544328133dae144cbd5d48b6ad3e6b45e588ec3b2478a6b8c60edd542fb82

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=sha256:903a94129c7b15a2ff1f6881fc7e8e7935a44eba78444e2034d06542b37c9190

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=sha256:363b9968ee375aa55986b4570f4d903ebf59f375e76f0a6b0b5f575885c795de

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.898187Z digest=sha256:bd961f630b8aa86d2c1f18f34903f79b21dc2f40ac55c671861c6f4739becfe2

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=sha256:90f32fd27dc656ff4938740f99fadd9f1170ad3f3f532af647e13978e0046dea

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=sha256:9754d0d597754cc484ce711159b179da6d748da4b229902d66ab21ee471f4c5d

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.912365Z digest=sha256:85a32827f60d55764d6c6611c1afeff53d50d8095f3da0f49b184d847eefcbd1

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.916916Z digest=sha256:432e2c5148d26b49ae1fcbedc1a1903c1c8dbd426a8ddf726ca7d480a0891a08

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.921603Z digest=sha256:b0f6761bbe35703682bc91751db6859c3fd67a4c6222c5a421431dd5674fd6ee

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:cbe107f17cc50725b9b72b802322745e812358f4b674784af5cc3ede1c96b27c

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.931744Z digest=sha256:77963cced59c86705d065d50249c242c11347e3b89d0c38d04cf6008713c16d7

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.936173Z digest=sha256:8952146307068ab77275dc0b06d7dc637760aaee9a08749fd1a8d785aefd4235

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.940416Z digest=sha256:9e44a4c6309696dee620a7e93d057234f01e38f1ff58f968779d02e97bc520fb

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.945057Z digest=sha256:735c7b51817af9351a376650a62e3e7de4e702f72c2509cb9a03961fa2d9d2f4

Pith citing papers

No inbound Pith citation observations are available.