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Paper Citation Record · LEDGER

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation

As of 8 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2508.07300.

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

pith.paper-citation-record.v1
2508.07300 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:16:29.604667Z

measured 27 of 27 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:16:29.520258Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T22:16:29.671993Z

Reference resolution

26 of 26 outbound references displayed

  • verified exact1
  • verified fuzzy17
  • unresolved7
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b04af57a-7649-4a41-989c-b5392bad862c · outbound

This paper cites an unresolved cited work.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-05T22:16:30.006648Z

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=2026-08-05T22:16:29.516202Z digest=sha256:47c5d2d701ccb7bd70d7a691aaee1d7b114f0e62603fba60d2bf2ef07391eee4

Observation 43753ea3-f346-47a6-8816-9fb5387ca6c2 · outbound

This paper cites The Deep Large Kernel Pyramid Pooling Module (DLKPPM) leverages large kernels for contextual enrichment.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation The Deep Large Kernel Pyramid Pooling Module (DLKPPM) leverages large kernels for contextual enrichment

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.995476Z

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.

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Observation 33873459-8383-4ad7-8d9f-445e28c789d7 · outbound

This paper cites an unresolved cited work.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-05T22:16:29.973074Z

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=2026-08-05T22:16:29.532271Z digest=sha256:f0ff1fdc8599c619d0c5b8ee8aa83e9fb5df968c742beee1842c004657b391bf

Observation 07e9665a-5602-49cf-8e32-78125fe3d3c2 · outbound

This paper cites an unresolved cited work.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-05T22:16:29.962322Z

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=2026-08-05T22:16:29.536218Z digest=sha256:c8f54f5e9ad211912bbe7a33589d78f0590cda11b7f16ff20b9871b4bbd288fe

Observation 61e4301e-347c-4aec-bf0a-5f705b894ab5 · outbound

This paper cites Bisenet v2: Bilateral network with guided aggregation for real-time seman- tic segmentation,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Bisenet v2: Bilateral network with guided aggregation for real-time seman- tic segmentation,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.908123Z

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=2026-08-05T22:16:29.553846Z digest=sha256:d668139a4142eca74321fb9ebfffd76c709ba97f2ec967bd2320a3e85017d889

Observation 8e3bc972-d540-48b4-b07b-2428063a18d0 · outbound

This paper cites Re- thinking bisenet for real-time semantic segmentation,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Re- thinking bisenet for real-time semantic segmentation,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.897884Z

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=2026-08-05T22:16:29.557453Z digest=sha256:ce20cad192da646f70345f117c4d9412d458d10f4ef54a84a610edc9717db6f4

Observation f2068cc3-482c-49e5-99ba-b72c751c1926 · outbound

This paper cites Fully convolutional networks for semantic segmenta- tion,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Fully convolutional networks for semantic segmenta- tion,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.951515Z

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=2026-08-05T22:16:29.539935Z digest=sha256:ba357768f77aad2b3166a0d56e4457128347c76e7cf4511973afd8449574dab8

Observation 5f92df68-9eba-4e57-8cad-9437d80ca1e3 · outbound

This paper cites U-net: Convolutional networks for biomedical im- age segmentation,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation U-net: Convolutional networks for biomedical im- age segmentation,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.940337Z

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=2026-08-05T22:16:29.543352Z digest=sha256:f20872dfb24bf02ece53fd98bbca05ce0d664d44d421486f0fca564e3b3ea68b

Observation 12870f03-7231-4307-b7e6-c88f434722a8 · outbound

This paper cites Pyramid scene parsing network,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Pyramid scene parsing network,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.928684Z

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=2026-08-05T22:16:29.547062Z digest=sha256:6930d1cb6e3087c84d456c8b5e88665f26b41a780d8c7d286d4b0d638eebe836

Observation 4367ad85-ebec-4cec-89bc-bf65ca3bf55c · outbound

This paper cites BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:16:29.677633Z

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=2026-08-05T22:16:29.520258Z digest=sha256:1c51d441a3f005d026b8372e0d9d21cdfa5b13099bd095517b19d5a66c33f3a0

Observation 09783046-bb00-40a5-81fb-885b72d46cb2 · outbound

This paper cites The cityscapes dataset for semantic urban scene understand- ing,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation The cityscapes dataset for semantic urban scene understand- ing,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.918252Z

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=2026-08-05T22:16:29.550572Z digest=sha256:d8834d7fa5e038b1f4c2ce7c8c3ce1d01473063b6d66c2feb8e1b271b25e2b19

Observation 28977110-88ff-4a02-b364-a65e34e8c6d9 · outbound

This paper cites More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T22:16:29.578467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:16:29.578467Z digest=sha256:e353c30d17ed9942259dd89f9d1a127f6b5489adc66dc90afc596edcf25ead0b

Observation b80a99fb-15c2-46f2-b7eb-09c2ca96c713 · outbound

This paper cites an unresolved cited work.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Unresolved cited work

Reference 13

Resolution
malformed identifier
raw_fallback, observed 2026-08-05T22:16:29.984553Z

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=2026-08-05T22:16:29.528230Z digest=sha256:20282d70a365a3107a4e1ffa1aebd715a86092305e8753f5255f97694d068a1d

Observation c60b886f-1be0-4e34-a4fa-f12532ec5ca8 · outbound

This paper cites Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T22:16:29.560996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:16:29.560996Z digest=sha256:1be035c80364ed534fa9d09d6d1ee4f6277caea94936553cc40a242d96eae5d3

Observation 8b52b329-4641-4ec5-b452-ca9ae3442842 · outbound

This paper cites Pidnet: A real-time semantic segmentation network inspired by pid controllers,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Pidnet: A real-time semantic segmentation network inspired by pid controllers,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.886452Z

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=2026-08-05T22:16:29.564729Z digest=sha256:a5f3e3bd8fddcba5b6b2ccb47ae0f77669bd8a30220320472da1e64b215f398b

Observation 39fed5a6-7d78-4e13-b889-215c34e41a70 · outbound

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

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-05T22:16:29.568474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:16:29.568474Z digest=sha256:1e543bdac6b8596d91c9c3b2604b067ee120a008c7a24b0f16ef929a928251aa

Observation 3fa5432b-f465-4380-bc36-818b2b64e177 · outbound

This paper cites Seaformer: Squeeze-enhanced axial trans- former for mobile semantic segmentation,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Seaformer: Squeeze-enhanced axial trans- former for mobile semantic segmentation,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.875485Z

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=2026-08-05T22:16:29.572068Z digest=sha256:54a4da9ba71d96f685d923459e61018e954a5c8cceefbf6535d5b96c11bb4174

Observation 24efacc9-7b22-434f-a62d-085f911ee86a · outbound

This paper cites Scaling up your kernels to 31x31: Re- visiting large kernel design in cnns,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Scaling up your kernels to 31x31: Re- visiting large kernel design in cnns,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.863555Z

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=2026-08-05T22:16:29.575426Z digest=sha256:871b639aa4cc8068b46eb347427197e4f9209bda43d085d3c4f26519a56b2785

Observation 7aa63b0b-2a23-4be9-8cab-e416fc214999 · outbound

This paper cites Visual attention net- work,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Visual attention net- work,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.852630Z

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.

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Observation c4184b24-cffd-4ff4-a7e8-878d92053368 · outbound

This paper cites Large separable kernel attention: Rethinking the large kernel attention design in cnn,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Large separable kernel attention: Rethinking the large kernel attention design in cnn,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.842559Z

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=2026-08-05T22:16:29.585476Z digest=sha256:e3896d451c967544e4eaf010da8a2493957c2d574590f884003b55c565ed9d27

Observation 96e5327a-4da3-4ec1-8c55-060a7cd20311 · outbound

This paper cites Large selective kernel network for remote sensing object detection,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Large selective kernel network for remote sensing object detection,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.735759Z

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=2026-08-05T22:16:29.588521Z digest=sha256:ba4b59091cc47db799802cb93a28e3e2820afda3d9c454cae0b5170a05c85372

Observation 7452633d-5647-427c-a97d-ee76ad6a160e · outbound

This paper cites Selective kernel networks,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Selective kernel networks,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.724601Z

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=2026-08-05T22:16:29.591541Z digest=sha256:ddc75d5783ff9466c152b311eb9aea86eaeb984021dac56ad9d64ac48dbdd110

Observation 17f98593-04b0-46f9-9456-ee5aae77b686 · outbound

This paper cites PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T22:16:29.594574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:16:29.594574Z digest=sha256:cea4b5f86bb0ad31e59792d6009692bbd1b75e73f6b696e9041301a3a1509922

Observation 8493340b-3629-4b7e-9e0e-ff928604ab46 · outbound

This paper cites Semantic flow for fast and accurate scene parsing,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Semantic flow for fast and accurate scene parsing,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.712721Z

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=2026-08-05T22:16:29.598252Z digest=sha256:22d8daf5e64756b27ab2e10bdb5227cf966e235bc653cb37538b9445887f7f4f

Observation f7acbe0d-7565-465c-a98d-af25623083c4 · outbound

This paper cites Semantic object classes in video: A high- definition ground truth database,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Semantic object classes in video: A high- definition ground truth database,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.700211Z

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=2026-08-05T22:16:29.601563Z digest=sha256:2bcb227bfd45bcc544e1fb04f99866984c8f84d4ca7a006bbaff2480b6a7ca9a

Observation 4b735723-6a76-4f9d-8691-dc5f44527a3d · outbound

This paper cites Imagenet large scale visual recognition challenge,.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation Imagenet large scale visual recognition challenge,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:16:29.689128Z

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=2026-08-05T22:16:29.604667Z digest=sha256:d0053a6e5d22617bed2135b9df3cd596804213b0a2788ef99920ce7e0bb49957

Pith citing papers

Observation 4367ad85-ebec-4cec-89bc-bf65ca3bf55c · inbound

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation cites this paper.

BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation BEVANet: Bilateral Efficient Visual Attention Network for Real-Time Semantic Segmentation

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:16:29.677633Z

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=2026-08-05T22:16:29.520258Z digest=sha256:1c51d441a3f005d026b8372e0d9d21cdfa5b13099bd095517b19d5a66c33f3a0