Paper Citation Record · LEDGER

Industrial Synthetic Segment Pre-training

As of 17 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2505.13099.

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

pith.paper-citation-record.v1
2505.13099 v2

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:25:36.289108Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

38 of 38 outbound references displayed

verified exact0
verified fuzzy26
unresolved12
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 87d0b158-e064-4cba-805f-526317c04d5d · outbound

This paper cites Synthseg: Segmentation of brain mri scans of any contrast and resolution without retraining.

Industrial Synthetic Segment Pre-training Synthseg: Segmentation of brain mri scans of any contrast and resolution without retraining

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.891669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1f36d1d7-eaa4-4195-a6fc-0cfad93b1469 · outbound

This paper cites Into the laion’s den: Investigating hate in multimodal datasets.

Industrial Synthetic Segment Pre-training Into the laion’s den: Investigating hate in multimodal datasets

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.878925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 68ab61bb-b4c3-456e-8b13-cfa19bb7bf01 · outbound

This paper cites Yolact: Real-time instance seg- mentation.

Industrial Synthetic Segment Pre-training Yolact: Real-time instance seg- mentation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.865512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ab8332a7-548e-416d-bea3-70db8929bfe5 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

Industrial Synthetic Segment Pre-training Emerging properties in self-supervised vision transformers

Reference 4

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Source-reported events for the cited work

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Observation c5292151-a0f4-477b-a412-f615426d6ef1 · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

Industrial Synthetic Segment Pre-training MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T20:25:36.157935Z

Source-reported events for the cited work

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Observation d861481e-db08-44df-b1a3-41ad6eddba69 · outbound

This paper cites Learning semantic segmentation from synthetic data: A geometrically guided input-output adaptation approach.

Industrial Synthetic Segment Pre-training Learning semantic segmentation from synthetic data: A geometrically guided input-output adaptation approach

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.842678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f2d3be73-bd73-4090-bf7f-cfdfd371dffb · outbound

This paper cites Masked-attention mask transformer for universal image segmentation.

Industrial Synthetic Segment Pre-training Masked-attention mask transformer for universal image segmentation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.829353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fc8d747c-b318-45c3-8c6c-39b8411101d6 · outbound

This paper cites Imagenet: A large- scale hierarchical image database.

Industrial Synthetic Segment Pre-training Imagenet: A large- scale hierarchical image database

Reference 8

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Source-reported events for the cited work

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Observation 7d91baed-1703-4b46-b5fd-fbd1008c08d3 · outbound

This paper cites Decaf: A deep convolutional activation feature for generic visual recognition.

Industrial Synthetic Segment Pre-training Decaf: A deep convolutional activation feature for generic visual recognition

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.807674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3d156b0c-655a-4258-a9e0-d4655d8a9867 · outbound

This paper cites Livecell—a large-scale dataset for label-free live cell segmentation.

Industrial Synthetic Segment Pre-training Livecell—a large-scale dataset for label-free live cell segmentation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.795062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8f6826ac-170d-48a1-a647-3e7cd05d4796 · outbound

This paper cites Mask r-cnn.

Industrial Synthetic Segment Pre-training Mask r-cnn

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T20:25:36.182615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c49b033-75dd-438d-9c78-b6b1bf83a6f4 · outbound

This paper cites Computer-Vision Benchmark Segment-Anything Model (SAM) in Medical Images: Accuracy in 12 Datasets.

Industrial Synthetic Segment Pre-training Computer-Vision Benchmark Segment-Anything Model (SAM) in Medical Images: Accuracy in 12 Datasets

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T20:25:36.186543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef2b773e-e28d-4b2d-a044-c70b24721a08 · outbound

This paper cites Segment anything is not always perfect: An investigation of sam on different real-world applications, 2024.

Industrial Synthetic Segment Pre-training Segment anything is not always perfect: An investigation of sam on different real-world applications, 2024

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.772457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6d10c17c-a93c-481d-8ed3-bd682f2ba01c · outbound

This paper cites Pre-training without natural images.

Industrial Synthetic Segment Pre-training Pre-training without natural images

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.759367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4be97f9a-fa91-47c2-b305-5a40494b11b5 · outbound

This paper cites Pre-training without natural images.

Industrial Synthetic Segment Pre-training Pre-training without natural images

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.746231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8ffbffae-03ad-41a8-b6d7-9fcb5ea56f46 · outbound

This paper cites Formula-driven supervised learning with recursive tiling patterns.

Industrial Synthetic Segment Pre-training Formula-driven supervised learning with recursive tiling patterns

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.732811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 06cb3762-b067-44a3-a21b-7ec74d6a1f57 · outbound

This paper cites Replacing labeled real-image datasets with auto-generated contours.

Industrial Synthetic Segment Pre-training Replacing labeled real-image datasets with auto-generated contours

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.719741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0c209a0a-4d50-4e08-9c05-2858c120b1ab · outbound

This paper cites Segment anything.

Industrial Synthetic Segment Pre-training Segment anything

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T20:25:36.209958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c492c97a-007b-4c56-88cb-46f2135da08a · outbound

This paper cites Industrial-iseg dataset, August 2024.

Industrial Synthetic Segment Pre-training Industrial-iseg dataset, August 2024

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.697641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a9e51dc5-907a-4605-b85f-6a267a5afb35 · outbound

This paper cites Microsoft coco: Common objects in context.

Industrial Synthetic Segment Pre-training Microsoft coco: Common objects in context

Reference 20

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Source-reported events for the cited work

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Observation 50a57b56-e38b-494e-9d1f-ae8174aaef0e · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Industrial Synthetic Segment Pre-training Swin transformer: Hierarchical vision transformer using shifted windows

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T20:25:36.221554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d28a545-2a1d-47ae-96e8-ae9d8cc0a0cb · outbound

This paper cites RTMDet: An Empirical Study of Designing Real-Time Object Detectors.

Industrial Synthetic Segment Pre-training RTMDet: An Empirical Study of Designing Real-Time Object Detectors

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T20:25:36.225452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c05be703-7972-42a1-be78-7e7716278ca8 · outbound

This paper cites Efficient load interference detection with limited labeled data.

Industrial Synthetic Segment Pre-training Efficient load interference detection with limited labeled data

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.668337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 71dd9d13-4f80-43c0-a641-f059885ae11d · outbound

This paper cites lightning-sam.

Industrial Synthetic Segment Pre-training lightning-sam

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.656085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1b99ae5d-5c07-4911-8228-12a08404ddd1 · outbound

This paper cites Adversarial learn- ing and self-teaching techniques for domain adaptation in semantic segmentation.

Industrial Synthetic Segment Pre-training Adversarial learn- ing and self-teaching techniques for domain adaptation in semantic segmentation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.643589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6bccc9f8-404a-4b0a-93d4-f2c1e7cf1187 · outbound

This paper cites Task2sim: Towards effective pre-training and transfer from synthetic data.

Industrial Synthetic Segment Pre-training Task2sim: Towards effective pre-training and transfer from synthetic data

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.630936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 498cea29-1615-4638-a888-a79f4f5d0fe1 · outbound

This paper cites The Endoscapes Dataset for Surgical Scene Segmentation, Object Detection, and Critical View of Safety Assessment: Official Splits and Benchmark.

Industrial Synthetic Segment Pre-training The Endoscapes Dataset for Surgical Scene Segmentation, Object Detection, and Critical View of Safety Assessment: Official Splits and Benchmark

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T20:25:36.244982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46a07838-3024-490e-ae41-c833eea4461b · outbound

This paper cites The segment anything model (sam) for remote sensing applications: From zero to one shot.

Industrial Synthetic Segment Pre-training The segment anything model (sam) for remote sensing applications: From zero to one shot

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.617944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 41186c70-0f3f-4f5f-b67b-08557fecf231 · outbound

This paper cites Segrcdb: Semantic segmentation via formula-driven supervised learning.

Industrial Synthetic Segment Pre-training Segrcdb: Semantic segmentation via formula-driven supervised learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.605216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3e8a7a17-5ad5-4769-b4b9-96350388d8a6 · outbound

This paper cites Visual atoms: Pre-training vision transformers with sinusoidal waves.

Industrial Synthetic Segment Pre-training Visual atoms: Pre-training vision transformers with sinusoidal waves

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.592462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f06d993b-4a05-440a-8a54-3ee8c84e7925 · outbound

This paper cites Stablerep: Syn- thetic images from text-to-image models make strong visual representation learners.Advances in Neural Information Processing Systems, 36, 2024.

Industrial Synthetic Segment Pre-training Stablerep: Syn- thetic images from text-to-image models make strong visual representation learners.Advances in Neural Information Processing Systems, 36, 2024

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.578743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 020f0a7d-d132-4947-9821-d0e0943706d6 · outbound

This paper cites Training deep networks with synthetic data: Bridging the reality gap by domain randomization.

Industrial Synthetic Segment Pre-training Training deep networks with synthetic data: Bridging the reality gap by domain randomization

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.564251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f99aca2f-e816-421e-b13c-9ffdb3b54d3f · outbound

This paper cites SpaceNet: A Remote Sensing Dataset and Challenge Series.

Industrial Synthetic Segment Pre-training SpaceNet: A Remote Sensing Dataset and Challenge Series

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T20:25:36.269333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf63d9db-a38b-4bd6-bb56-d502e2fe077c · outbound

This paper cites Mv-fractaldb: formula-driven supervised learning for multi- view image recognition.

Industrial Synthetic Segment Pre-training Mv-fractaldb: formula-driven supervised learning for multi- view image recognition

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.551316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7bb69284-8540-48dd-8419-15da662ae14a · outbound

This paper cites Towards fairer datasets: Filtering and balancing the distribution of the people subtree in the imagenet hierarchy.

Industrial Synthetic Segment Pre-training Towards fairer datasets: Filtering and balancing the distribution of the people subtree in the imagenet hierarchy

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T20:25:36.277349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4fdc9f7-e3ad-4fb7-8b26-5e7867c4913c · outbound

This paper cites Seggen: Supercharg- ing segmentation models with text2mask and mask2img synthesis.

Industrial Synthetic Segment Pre-training Seggen: Supercharg- ing segmentation models with text2mask and mask2img synthesis

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.538035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3bebccfd-d740-41f4-a506-358c64303f6f · outbound

This paper cites Ts-sam: Fine-tuning segment-anything model for downstream tasks.

Industrial Synthetic Segment Pre-training Ts-sam: Fine-tuning segment-anything model for downstream tasks

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.525065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c8a9cd5a-58a9-4901-b925-27bcd096c5a7 · outbound

This paper cites Scene parsing through ade20k dataset.

Industrial Synthetic Segment Pre-training Scene parsing through ade20k dataset

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:25:36.511457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.