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Paper Citation Record · LEDGER

Lightweight Road Environment Segmentation using Vector Quantization

As of 19 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2504.14113.

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

pith.paper-citation-record.v1
2504.14113 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:00:05.447364Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

30 of 30 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2eef1d5a-aa85-43d2-81f7-84049d5c74ef · outbound

This paper cites write newline.

Lightweight Road Environment Segmentation using Vector Quantization write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:00:05.315031Z digest=sha256:266f5887f60c48e73fabfcf8a7f0797cee6e6c488ff08b47a4f1b2e767d87758

Observation 9763bb00-0a41-4e81-8846-5d84283417ad · outbound

This paper cites Segnet: A deep convolutional encoder-decoder architecture for image segmentation.

Lightweight Road Environment Segmentation using Vector Quantization Segnet: A deep convolutional encoder-decoder architecture for image segmentation

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 2b7d869c-0cbd-4385-8d21-331b753ffc5d · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

Lightweight Road Environment Segmentation using Vector Quantization TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 3

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no resolver link, observed 2026-08-16T12:00:05.325575Z

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Observation ba55cf18-160a-4e5f-a900-7f0666864fc8 · outbound

This paper cites L., 2017.

Lightweight Road Environment Segmentation using Vector Quantization L., 2017

Reference 4

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-16T12:00:05.330516Z digest=sha256:efa64f2155f7bceac062d68711e88c3d758e7b2ac6fc2fd47ece03b46f0d2201

Observation c9fdd28d-a7bd-40de-b6c7-cedec219bccf · outbound

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

Lightweight Road Environment Segmentation using Vector Quantization An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

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Unavailable: canonical work link unavailable.

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Observation a5720822-d0a0-4d65-af68-b4c04b82a47d · outbound

This paper cites Synergynet: Bridging the gap between discrete and continuous representations for precise medical image segmentation.

Lightweight Road Environment Segmentation using Vector Quantization Synergynet: Bridging the gap between discrete and continuous representations for precise medical image segmentation

Reference 6

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 4aeb7268-b49e-467a-a175-fc1fbb4122d6 · outbound

This paper cites Denoising diffusion probabilistic models.

Lightweight Road Environment Segmentation using Vector Quantization Denoising diffusion probabilistic models

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 985e5408-88c4-4c20-a9b4-53ebab11bb5e · outbound

This paper cites Fully convolutional networks for semantic segmentation.

Lightweight Road Environment Segmentation using Vector Quantization Fully convolutional networks for semantic segmentation

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T12:00:05.349156Z digest=sha256:e8fdbc7d3ab9df9d6ab4bb51078e7a6df7bb90c6f1b06e76a8be83edb6817bed

Observation e935101b-9bf5-468c-88b3-cf41c6c2a78e · outbound

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

Lightweight Road Environment Segmentation using Vector Quantization MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

Reference 9

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Observation 3c7fc33c-e252-4fcc-a5fa-5113b11a17d6 · outbound

This paper cites Finite Scalar Quantization: VQ-VAE Made Simple.

Lightweight Road Environment Segmentation using Vector Quantization Finite Scalar Quantization: VQ-VAE Made Simple

Reference 10

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Observation c29e4232-fac0-4b96-add4-cbeb823d53c0 · outbound

This paper cites KnobGen: Controlling the Sophistication of Artwork in Sketch-Based Diffusion Models.

Lightweight Road Environment Segmentation using Vector Quantization KnobGen: Controlling the Sophistication of Artwork in Sketch-Based Diffusion Models

Reference 11

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Unavailable: canonical work link unavailable.

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Observation 6e01e434-bedb-4f7a-b122-415964111454 · outbound

This paper cites A Probabilistic-based Drift Correction Module for Visual Inertial SLAMs.

Lightweight Road Environment Segmentation using Vector Quantization A Probabilistic-based Drift Correction Module for Visual Inertial SLAMs

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 4c146477-4d00-48be-bc33-34ce905faea0 · outbound

This paper cites MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image Segmentation.

Lightweight Road Environment Segmentation using Vector Quantization MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image Segmentation

Reference 13

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Observation 105d47f5-ac5c-41bc-86ed-a3d720943d65 · outbound

This paper cites Segformer3d: An efficient transformer for 3d medical image segmentation.

Lightweight Road Environment Segmentation using Vector Quantization Segformer3d: An efficient transformer for 3d medical image segmentation

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 647d74e3-8fd2-4c8b-a687-31c430f09e47 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Lightweight Road Environment Segmentation using Vector Quantization High-resolution image synthesis with latent diffusion models

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 635da012-7367-4439-870f-d0636edd0240 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Lightweight Road Environment Segmentation using Vector Quantization U-net: Convolutional networks for biomedical image segmentation

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 529f7831-f9b1-4736-9843-0ad62756d218 · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

Lightweight Road Environment Segmentation using Vector Quantization Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation fb46c6d3-a9f6-46a2-a4af-6245d739ceee · outbound

This paper cites Vector quantisation for robust segmentation.

Lightweight Road Environment Segmentation using Vector Quantization Vector quantisation for robust segmentation

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation d376807e-38af-4628-805a-cb3b2e52b9d5 · outbound

This paper cites Spatial-aware feature aggregation for image based cross-view geo-localization.

Lightweight Road Environment Segmentation using Vector Quantization Spatial-aware feature aggregation for image based cross-view geo-localization

Reference 19

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Observation 54c4c53d-0126-44cb-8f00-d401040a5f37 · outbound

This paper cites Segmenter: Transformer for semantic segmentation.

Lightweight Road Environment Segmentation using Vector Quantization Segmenter: Transformer for semantic segmentation

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3bcf16dc-ffda-4f30-8556-acf7b574281e · outbound

This paper cites et al., 2017.

Lightweight Road Environment Segmentation using Vector Quantization et al., 2017

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ac6011b3-35bf-4786-b684-512fddd667f9 · outbound

This paper cites Attention is all you need.

Lightweight Road Environment Segmentation using Vector Quantization Attention is all you need

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4121e9c5-c72f-4ce4-8cdf-98e5ec24a0d1 · outbound

This paper cites Transbts: Multimodal brain tumor segmentation using transformer.

Lightweight Road Environment Segmentation using Vector Quantization Transbts: Multimodal brain tumor segmentation using transformer

Reference 23

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T12:00:05.416407Z digest=sha256:b459c3362f4423aa6cb573ccf95eaee2fd8a4eb5d8305ea027b5bd149b771f80

Observation 1c347595-1612-40f3-901f-06b66bbdc374 · outbound

This paper cites M., Luo, P., 2021.

Lightweight Road Environment Segmentation using Vector Quantization M., Luo, P., 2021

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T12:00:05.420769Z digest=sha256:88b4589c3188a2d3691f7a505b7b792f4d7e3a12d6856d18988bbe4cce6a1fa6

Observation ecef1e8f-b6ab-4b74-93a5-32b7ff9dfc88 · outbound

This paper cites HiFi-Codec: Group-residual Vector quantization for High Fidelity Audio Codec.

Lightweight Road Environment Segmentation using Vector Quantization HiFi-Codec: Group-residual Vector quantization for High Fidelity Audio Codec

Reference 25

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Unavailable: canonical work link unavailable.

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Observation c6f95ef8-0c11-43fa-b3f9-313b5eb35ca3 · outbound

This paper cites Vector-quantized Image Modeling with Improved VQGAN.

Lightweight Road Environment Segmentation using Vector Quantization Vector-quantized Image Modeling with Improved VQGAN

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a08295c1-094d-46aa-9f4f-ce917f632c38 · outbound

This paper cites Soundstream: An end-to-end neural audio codec.

Lightweight Road Environment Segmentation using Vector Quantization Soundstream: An end-to-end neural audio codec

Reference 27

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation a3930c9c-4d14-46a5-b601-467644c86508 · outbound

This paper cites Transfuse: Fusing transformers and cnns for medical image segmentation.

Lightweight Road Environment Segmentation using Vector Quantization Transfuse: Fusing transformers and cnns for medical image segmentation

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 5f9b78e6-88d1-48cc-9418-3852acdccf81 · outbound

This paper cites Vigor: Cross-view image geo-localization beyond one-to-one retrieval.

Lightweight Road Environment Segmentation using Vector Quantization Vigor: Cross-view image geo-localization beyond one-to-one retrieval

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T12:00:05.443083Z digest=sha256:12ae8f60d419fd9df8661081dbc132fe03e24250e120b86495d5f64e5a0e0adb

Observation d716a269-d404-49aa-92d3-d4736371e89f · outbound

This paper cites K., Yilmaz, A., 2024.

Lightweight Road Environment Segmentation using Vector Quantization K., Yilmaz, A., 2024

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Pith citing papers

No inbound Pith citation observations are available.