Paper Citation Record · LEDGER

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

As of 10 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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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.

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 2026-08-10T06:31:04.303077+00:00.

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.

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 2026-08-10T06:31:04.303077+00:00.

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.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

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