Paper Citation Record · LEDGER

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling

As of 17 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2506.13282.

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

pith.paper-citation-record.v1
2506.13282 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:41:26.063983Z

measured 41 of 41 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:41:25.903981Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T00:41:26.141031Z

Reference resolution

40 of 40 outbound references displayed

verified exact1
verified fuzzy33
unresolved4
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d72eb9aa-8a78-49b5-b8d5-5cb0360e6e51 · outbound

This paper cites Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T00:41:26.145499Z

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 20dd9dcc-e9e0-4a0f-bb7c-9db4d0f16276 · outbound

This paper cites In particular, CLIP [15] is often utilized due to its aligned feature space for text and images.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling In particular, CLIP [15] is often utilized due to its aligned feature space for text and images

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.646143Z

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 3c918bf7-c763-44d0-a9eb-193b6bcf8773 · outbound

This paper cites object which is made of steel.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling object which is made of steel

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.635511Z

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 373f3bea-a247-4b77-bcec-558ab4172e25 · outbound

This paper cites Setup Dataset and Metrics.The images used in this study were collected from a steel scrap recycling site and provided by anonymized.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Setup Dataset and Metrics.The images used in this study were collected from a steel scrap recycling site and provided by anonymized

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.613829Z

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 7304043d-ff9d-43b1-af4d-ec47f12ecdfa · outbound

This paper cites an unresolved cited work.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:41:26.591644Z

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 789257ed-a2fd-48db-83b0-cd9a1eb484b3 · outbound

This paper cites object which is not steel.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling object which is not steel

Reference 6

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T00:41:26.602003Z

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 277248d6-069d-4109-aaef-e0c84045290b · outbound

This paper cites Padim: A patch distribution modeling frame- work for anomaly detection and localization,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Padim: A patch distribution modeling frame- work for anomaly detection and localization,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.426682Z

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 3711062d-7d45-4970-80dc-ac2e4f0d1da6 · outbound

This paper cites Climate change and the production of iron and steel,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Climate change and the production of iron and steel,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.581389Z

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 f5278243-1d9d-479b-b63f-14ae8383fa61 · outbound

This paper cites Scrap and the steel industry,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Scrap and the steel industry,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.570994Z

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 ca78b1a3-37ba-40e3-8ca9-0b19b7f23c0b · outbound

This paper cites A Subspace Projection Approach to Autoencoder-based Anomaly Detection.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling A Subspace Projection Approach to Autoencoder-based Anomaly Detection

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:41:26.129445Z

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 bbb71eda-7e71-4043-b5f7-956fa3e9f600 · outbound

This paper cites Ganomaly: Semi-supervised anomaly detection via adversar- ial training,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Ganomaly: Semi-supervised anomaly detection via adversar- ial training,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.559358Z

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 e0666ddd-13ee-4f98-ae79-c53c16a2eb09 · outbound

This paper cites Skip-ganomaly: Skip connected and adversari- ally trained encoder-decoder anomaly detection,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Skip-ganomaly: Skip connected and adversari- ally trained encoder-decoder anomaly detection,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.547583Z

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 3790d65b-0cef-4562-b5b7-633d283b24db · outbound

This paper cites Anomalyd- iffusion: Few-shot anomaly image generation with diffusion model,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Anomalyd- iffusion: Few-shot anomaly image generation with diffusion model,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.536410Z

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 b98d1654-8b24-49ce-be49-e00e38987957 · outbound

This paper cites Beyond dents and scratches: Log- ical constraints in unsupervised anomaly detection and local- ization,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Beyond dents and scratches: Log- ical constraints in unsupervised anomaly detection and local- ization,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.368867Z

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 6158a06b-1fbd-46c6-9185-34d15f7f0a04 · outbound

This paper cites Towards total recall in industrial anomaly detection,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Towards total recall in industrial anomaly detection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.416107Z

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 0fb5c67c-4239-422b-9ea9-4cc960841783 · outbound

This paper cites Segment Any Anomaly without Training via Hybrid Prompt Regularization.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Segment Any Anomaly without Training via Hybrid Prompt Regularization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T00:41:25.970590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 639543f5-bcc6-4192-b998-3228c196ed5f · outbound

This paper cites APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T00:41:25.974727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b73fa6f0-a8ce-458a-9aa1-c41aab58f254 · outbound

This paper cites Winclip: Zero- /few-shot anomaly classification and segmentation,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Winclip: Zero- /few-shot anomaly classification and segmentation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.404538Z

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 508ae3c6-c002-44de-95b0-66761aa0fe99 · outbound

This paper cites Then, they are further divided into patch images.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Then, they are further divided into patch images

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.624630Z

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 18d8a3a8-926f-413f-9656-f14535898bdc · outbound

This paper cites Mvtec ad — a comprehensive real-world dataset for unsupervised anomaly detection,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Mvtec ad — a comprehensive real-world dataset for unsupervised anomaly detection,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.391251Z

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 dbead3b9-c7ce-43a5-8caa-38afccbafb64 · outbound

This paper cites Spot-the-difference self-supervised pre- training for anomaly detection and segmentation,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Spot-the-difference self-supervised pre- training for anomaly detection and segmentation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.379788Z

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 01c2684d-8704-4125-8b9a-1c7f35497e19 · outbound

This paper cites Learning transferable visual models from nat- ural language supervision,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Learning transferable visual models from nat- ural language supervision,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.356832Z

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 8a9aa162-6a26-497f-9c8d-3d1d43769100 · outbound

This paper cites BLIP: Bootstrapping language-image pre-training for unified vision-language understanding and generation,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling BLIP: Bootstrapping language-image pre-training for unified vision-language understanding and generation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.344276Z

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 907a4e7c-66e6-4a4c-9617-1cdb415d0c82 · outbound

This paper cites BLIP-2: Bootstrapping language-image pre-training with frozen image encoders and large language models,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling BLIP-2: Bootstrapping language-image pre-training with frozen image encoders and large language models,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.332902Z

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 6132d185-60fd-426a-9e30-58a0c7ba8c10 · outbound

This paper cites Anomalyclip: Object-agnostic prompt learning for zero-shot anomaly detection,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Anomalyclip: Object-agnostic prompt learning for zero-shot anomaly detection,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.321479Z

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 182b0f7e-f3e3-427e-aaca-47cf1ca67965 · outbound

This paper cites lang-segment-anything,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling lang-segment-anything,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.311116Z

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 3f05b12a-695f-4fc8-ae38-e55bbbfb9aaa · outbound

This paper cites Segment anything,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Segment anything,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.300538Z

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 172f58cf-8e26-4fee-b631-c5f8b187baa8 · outbound

This paper cites Thickness classifier on steel in heavy melting scrap by deep-learning-based image analysis,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Thickness classifier on steel in heavy melting scrap by deep-learning-based image analysis,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.289055Z

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 b106905c-5b37-42a0-bd12-803b5463ca9c · outbound

This paper cites Waveseg- net: An efficient method for scrap steel segmentation utilizing wavelet transform and multiscale focusing,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Waveseg- net: An efficient method for scrap steel segmentation utilizing wavelet transform and multiscale focusing,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.278199Z

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 22e1570d-e812-4c57-a1c8-e7e9b3b69a99 · outbound

This paper cites Au- tomated scrap steel grading via a hierarchical learning-based framework,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Au- tomated scrap steel grading via a hierarchical learning-based framework,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.266068Z

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 f0aa0d38-740a-4488-afa7-6b93fe563380 · outbound

This paper cites Pyramid scene parsing network,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Pyramid scene parsing network,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.255328Z

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 59aa89e1-3929-4e9e-9229-52bab1b28e89 · outbound

This paper cites Clipsam: Clip and sam collaboration for zero- shot anomaly segmentation,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Clipsam: Clip and sam collaboration for zero- shot anomaly segmentation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.244783Z

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 c844c76d-793b-49b1-90e3-592a8fe5dad7 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.234000Z

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 8ca3cd60-2d24-4d70-9444-41ae59723069 · outbound

This paper cites The Road Less Scheduled.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling The Road Less Scheduled

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T00:41:26.038271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56f8a27a-564c-47cc-a9d5-bf1a2b3f4723 · outbound

This paper cites Decoupled weight decay regularization,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Decoupled weight decay regularization,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.221751Z

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 b563e1f0-62f7-4a7a-9bed-b18671234410 · outbound

This paper cites Class-balanced loss based on effective number of samples,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Class-balanced loss based on effective number of samples,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.210159Z

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 5cd12e41-aea8-4070-8d77-f2e8d8bf4b82 · outbound

This paper cites Dice loss for data-imbalanced NLP tasks,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Dice loss for data-imbalanced NLP tasks,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.198255Z

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 1b2cda99-18ed-4320-91d7-f2ed025dbbbe · outbound

This paper cites Yolov8 by ultralytics,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Yolov8 by ultralytics,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.185821Z

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 d56fd7e8-8369-4c57-9397-ab8867c24808 · outbound

This paper cites Yolov11 by ultralytics,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Yolov11 by ultralytics,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.173534Z

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 be4dd0ae-6632-4a29-aaf6-c708c759b519 · outbound

This paper cites Mask r-cnn,.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling Mask r-cnn,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:41:26.162138Z

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

Observation d72eb9aa-8a78-49b5-b8d5-5cb0360e6e51 · inbound