Paper Citation Record · LEDGER

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation

As of 15 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2505.16540.

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

pith.paper-citation-record.v1
2505.16540 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:02:54.730471Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

34 of 34 outbound references displayed

verified exact0
verified fuzzy24
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation afe0bd4a-5007-4656-a295-5e276b1f4c62 · outbound

This paper cites Fowlkes, and Jitendra Malik.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Fowlkes, and Jitendra Malik

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:58.199384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e22671b8-9ad8-4bd8-8a9a-b9edf624891d · outbound

This paper cites Metal- lography and crystallographic texture analysis.The Encyclo- pedia of Archaeological Sciences, pages 1–4, 2018.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Metal- lography and crystallographic texture analysis.The Encyclo- pedia of Archaeological Sciences, pages 1–4, 2018

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:58.046127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 16ad1ea2-13c2-4d60-8af3-205454c7d28e · outbound

This paper cites Deepedge: A multi-scale bifurcated deep network for top- down contour detection.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Deepedge: A multi-scale bifurcated deep network for top- down contour detection

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:57.895625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 471e2664-68de-42c4-9a54-d3b42bf237d9 · outbound

This paper cites Texture analysis of medical images.Clinical radiology, 59(12):1061–1069, 2004.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Texture analysis of medical images.Clinical radiology, 59(12):1061–1069, 2004

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:57.751198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 73bf06ad-e63a-4ecf-b69a-3413a4703959 · outbound

This paper cites Cimpoi, S.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Cimpoi, S

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T15:02:52.125359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 624ea1bc-6760-4b70-ab3b-b1dfedf8a693 · outbound

This paper cites De- scribing textures in the wild.Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 3606–3613, 2014.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation De- scribing textures in the wild.Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 3606–3613, 2014

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:57.635217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bd21a122-3ec9-4e44-8b09-6c511a2cada0 · outbound

This paper cites Avoiding post-processing with context: Texture boundary detection in metallography.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Avoiding post-processing with context: Texture boundary detection in metallography

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:57.459855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 80d05a22-3a9b-43d9-b37b-9727ba0010fc · outbound

This paper cites Mining textural knowl- edge in biological images: Applications, methods and trends.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Mining textural knowl- edge in biological images: Applications, methods and trends

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:57.360178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b2b7eeb7-0000-4137-8481-e587cceb9a61 · outbound

This paper cites an unresolved cited work.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:02:57.204847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0ff1e609-534a-41f2-81c8-74fe63e866b8 · outbound

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

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T15:02:52.588706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 521ebeb9-1d0f-4d04-b128-c05390db80af · outbound

This paper cites an unresolved cited work.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:02:57.087244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 63cf50e5-78c6-4775-abac-8578483dc93d · outbound

This paper cites Can We Talk Models Into Seeing the World Differently?.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Can We Talk Models Into Seeing the World Differently?

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T15:02:52.741800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 377c2400-5812-4eb0-bb13-8070c167edaa · outbound

This paper cites Imagenet-trained cnns are biased towards texture; increasing shape bias improves accuracy and robustness.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Imagenet-trained cnns are biased towards texture; increasing shape bias improves accuracy and robustness

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:56.931176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7f83cf7a-ebff-4309-8da5-33714258ba23 · outbound

This paper cites Bdcn: Bi-directional cascade network for per- ceptual edge detection.IEEE Transactions on Pattern Anal- ysis and Machine Intelligence, 44(1):100–113, 2022.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Bdcn: Bi-directional cascade network for per- ceptual edge detection.IEEE Transactions on Pattern Anal- ysis and Machine Intelligence, 44(1):100–113, 2022

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:56.783167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 127435f9-4322-42f3-99e8-9d079d0a567f · outbound

This paper cites Segment Anything Model for Medical Images?.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Segment Anything Model for Medical Images?

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T15:02:53.009675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74a202c9-dfed-4ae5-b5fd-6b5335690176 · outbound

This paper cites Segment anything model for medical images?Medical Image Analysis, 92:103061, 2024.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Segment anything model for medical images?Medical Image Analysis, 92:103061, 2024

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:02:53.108861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3668f6a-a9d5-4170-aa87-1d2130cf4688 · outbound

This paper cites Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T15:02:53.203778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a7cae47-123b-4033-84cd-266dd0a1e8da · outbound

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

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Segment anything is not always perfect: An investi- gation of sam on different real-world applications, 2024

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:56.636158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e2e35e86-ec0a-4b22-aa33-ba344cc734f6 · outbound

This paper cites Recent advances on image edge detec- tion: A comprehensive review.Neurocomputing, 2022.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Recent advances on image edge detec- tion: A comprehensive review.Neurocomputing, 2022

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:56.514283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7367107d-dc0b-4ad3-a402-0efed8029f0e · outbound

This paper cites Learned shape-tailored descriptors for segmentation.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Learned shape-tailored descriptors for segmentation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:56.428872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c8621fd3-c0f0-411c-8816-340e583bc539 · outbound

This paper cites Segment any- thing.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Segment any- thing

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:56.310424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ba2d915b-b0d9-4cfa-b1e6-096686a58d28 · outbound

This paper cites Pushing the boundaries of boundary de- tection using deep learning.arXiv: Computer Vision and Pattern Recognition, 2015.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Pushing the boundaries of boundary de- tection using deep learning.arXiv: Computer Vision and Pattern Recognition, 2015

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:56.212050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9727b57e-d5eb-4cd2-b5a2-2014a01ffab0 · outbound

This paper cites Segment anything in medical images.Na- ture Communications, 15(1):44824, 2024.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Segment anything in medical images.Na- ture Communications, 15(1):44824, 2024

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:56.102989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ef3cb91c-9f9b-4e7b-9011-aea54496dac1 · outbound

This paper cites Martin, C.C.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Martin, C.C

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:55.974979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 355e4a80-4d39-4c55-89de-b702a14a0909 · outbound

This paper cites Have we solved edge detection? a review of state-of-the-art datasets and dnn based techniques.IEEE Access, 10:70541– 70555, 2022.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Have we solved edge detection? a review of state-of-the-art datasets and dnn based techniques.IEEE Access, 10:70541– 70555, 2022

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:55.914027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation df35f0b9-bfe0-40ce-9f0d-7ea901f1a121 · outbound

This paper cites Intriguing properties of vision transform- ers.Advances in Neural Information Processing Systems, 34: 23296–23308, 2021.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Intriguing properties of vision transform- ers.Advances in Neural Information Processing Systems, 34: 23296–23308, 2021

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:55.765038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6a291fd3-456f-4cce-9867-a962e4fc329b · outbound

This paper cites Edter: Edge detection with transformer.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Edter: Edge detection with transformer

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:55.622336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1fc85fb9-dc36-48e1-a7ef-6d7d5f39483d · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation SAM 2: Segment Anything in Images and Videos

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:02:54.184787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 461a7af9-6d67-4653-bf49-420acacfea91 · outbound

This paper cites An end-to- end computer vision methodology for quantitative metallog- raphy.Scientific Reports, 12(1):4776, 2022.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation An end-to- end computer vision methodology for quantitative metallog- raphy.Scientific Reports, 12(1):4776, 2022

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:55.482317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2047ba2a-e280-45b7-b5d9-36c46b10019a · outbound

This paper cites Universal semantic-less texture boundary detection for mi- croscopy (and metallography).

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Universal semantic-less texture boundary detection for mi- croscopy (and metallography)

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:55.379384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e206be4e-23df-42c9-8cf1-78e208e12565 · outbound

This paper cites Deepcontour: A deep convolutional fea- ture learned by positive-sharing loss for contour detection.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Deepcontour: A deep convolutional fea- ture learned by positive-sharing loss for contour detection

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:55.319154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0911a3f1-1d61-4393-ac57-d3bba3291196 · outbound

This paper cites Compositional neural textures.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Compositional neural textures

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:55.166476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 995e95d9-4e6b-4063-b634-24e1d5b53cdb · outbound

This paper cites Scene parsing through ade20k dataset.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Scene parsing through ade20k dataset

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T15:02:54.606467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 927c99e3-6b37-47cd-82e6-1972ca3cfd4e · outbound

This paper cites Scene parsing through ade20k dataset.Proceedings of the IEEE Confer- ence on Computer Vision and Pattern Recognition (CVPR), pages 633–641, 2017.

TextureSAM: Towards a Texture Aware Foundation Model for Segmentation Scene parsing through ade20k dataset.Proceedings of the IEEE Confer- ence on Computer Vision and Pattern Recognition (CVPR), pages 633–641, 2017

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:02:55.000206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.