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Paper Citation Record · LEDGER

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms

As of 13 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 2026-08-13T06:32:02.005865+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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.764004Z digest=sha256:7ee98b5cbfb66f793397dfcf2834cb0de2279082cdcfa6844585732421e02bdf

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.768993Z digest=sha256:06873f402e74733e41e1e2847bd86bd0598ba1188d95896e69ea5793f03b029c

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

Resolution
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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.778978Z digest=sha256:7820dd40690893252ffc478ef1567444448450dc01d1daba7aef45ed74fd7798

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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unresolved
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:c71fdadd449174e49f4a2bf90e0c77bba4d69a5f5a4f9cc3bcd3534a43ca293f

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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verified fuzzy
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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.789439Z digest=sha256:c773f1ce38f9de345c7e7ddba65fa978afbc8e66cbe1b6b48dc1a0f62b3b7d2c

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.794084Z digest=sha256:427770087280616ac04ff2f0836a74d208168b5d5c165b45a098195444b21168

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.798724Z digest=sha256:e0ebecd8f855fee9535e3b80535e00b584699deb5fb3becc37aee7ccc6dfc22d

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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verified fuzzy
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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.803335Z digest=sha256:452ced922050c6caece906796b47101cf099dead8d814a732d6309435b1686aa

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=sha256:80fbf8335c1efb78dff3100a2bdab554730085b1921b928d74005f5ab2781e7d

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.814256Z digest=sha256:39f75e91ff580357214e4656631339dec1117fe2a68dcf84b3131002a7eb81a8

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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unresolved
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:bd2ab3d54d02df8e67557b3dc3da837e20d835b42939485cc59a3310074bb7d8

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.824159Z digest=sha256:f11aada1b7920dd52a638ce03aadb8abcca87e1031cae04d0777a45ca1b1c584

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=sha256:02d7b024b2a19cf992cdec5bce53caf42808bc7601993c06036a7f4666bacfa6

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.834071Z digest=sha256:573ea7124bbfe118b89def59292a61dbf932f69fb63a8e35998de49b11d7318e

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.838617Z digest=sha256:08167c288bad064096dbe090ff4b2170394f939bb646fcfe1d1afc8c02284726

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=sha256:862e1a3b44231383dbc9702686ad0295dc2778c21b3c2d10eef1e7cccbe96d05

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

Resolution
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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.847408Z digest=sha256:7f7069aa2b12dfb2efa68cd44b89ec70048052f3c4cfabcce5cea781dfa68ffe

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

Resolution
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 2026-08-13T06:32:02.005865+00:00.

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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

Resolution
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 2026-08-13T06:32:02.005865+00:00.

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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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.860766Z digest=sha256:bd2c16a5714440d79be1fce4b35e6a8054e68da055ea1da4425e5bfba4a208b3

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=sha256:7f7b4e8e9fbe80f79c40a1ec1b49cf0884e2812477eb00a322fd25b78416b950

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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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:cb644ee1b2bc0e5cf692f670de3a0b5bcf2901659fc42ea09f062217ae119b09

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

Resolution
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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.883017Z digest=sha256:8d87801adce4904986b8c55a3e5b69918949dea6681e5549b6b0fe26472dbd9d

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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unresolved
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:eb5e2fc8face5a9d5e31680db2db0299ee17aef479d48ddea90d7adff6cffb79

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

Resolution
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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.898187Z digest=sha256:ce4767a5d32b69f4233cf866cc16fe05fc82faafa879b49cedc6e69f65ec1c04

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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unresolved
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:b4476380573d89d584bf475a1f85b446c70c099f90ebe3d155b4a18ed6dcd866

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

Resolution
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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.912365Z digest=sha256:95ee52770fff87975ba214a93ca8435faa0554415a9162174abcb70cf772584a

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.916916Z digest=sha256:1911035edd2685e3dc7d71aaf0d3305a12138f6294ee6bd1fcc7262deeac43f3

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

Resolution
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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.921603Z digest=sha256:2f4bfcbc7db3024d757558e2a6669113707d6e267b80f0c1b271fcb0f7961dba

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.931744Z digest=sha256:45e2e49082f6ba0d76f02630bc6dde46d5055143016981a85f0d2f940807320d

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.936173Z digest=sha256:016c2696f2b53bfdff6ee3cbc032af8c4beb637a19470b84daf50c5cd8e25549

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.940416Z digest=sha256:68d3103f4bc1a15e15c9c7d05796dd87edab137c351e2a4b633d4ed9d3622fa7

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-06T05:44:19.945057Z digest=sha256:a82bc67c699e0a10776e1d4559123e9316f4146af2187900df1cf643f8f98e45

Pith citing papers

No inbound Pith citation observations are available.