Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T20:33:30.327946Z
Paper Citation Record · LEDGER
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma
As of 18 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2501.08042.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
21 of 21 outbound references displayed
- verified exact0
- verified fuzzy19
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation fd10bd31-0ed4-4d82-a703-4a5d687e06e0 · outbound
This paper cites The epidemiology of sarcoma,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma The epidemiology of sarcoma,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:32.868040Z
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 c57e1e87-64aa-46e0-a3ca-65b9a5db92d1 · outbound
This paper cites Ewing tumour: incidence, prognosis and treatment options,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Ewing tumour: incidence, prognosis and treatment options,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:32.718706Z
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 df95a33d-a38b-4577-9218-17850c56266f · outbound
This paper cites Changes in incidence and survival of ewing sarcoma patients over the past 3 decades: Surveillance epidemiology and end results data,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Changes in incidence and survival of ewing sarcoma patients over the past 3 decades: Surveillance epidemiology and end results data,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:32.644269Z
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 d5bdc2b1-9452-43dc-aead-2af7955971d5 · outbound
This paper cites Two-phase deep learning algorithm for detection and differentiation of ewing sarcoma and acute osteomyeli- tis in paediatric radiographs,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Two-phase deep learning algorithm for detection and differentiation of ewing sarcoma and acute osteomyeli- tis in paediatric radiographs,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:32.421318Z
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 04e59038-a08a-456a-83c0-3fb681e77371 · outbound
This paper cites Machine learning for rhabdomyosarcoma histopathology,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Machine learning for rhabdomyosarcoma histopathology,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:32.208013Z
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 d9c5b28a-6726-4604-aaa6-13e0f54371e8 · outbound
This paper cites Deep learning of rhab- domyosarcoma pathology images for classification and survival outcome predic- tion,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Deep learning of rhab- domyosarcoma pathology images for classification and survival outcome predic- tion,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:32.026445Z
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 19b8dda7-b755-405f-88b4-841baf701bd3 · outbound
This paper cites Predicting molecular subtype and survival of rhabdomyosarcoma patients using deep learning of h&e images: A report from the children’s oncology group,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Predicting molecular subtype and survival of rhabdomyosarcoma patients using deep learning of h&e images: A report from the children’s oncology group,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:31.879696Z
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 608d949f-8a86-4367-bb97-82ac813fea75 · outbound
This paper cites Deep learning based automated tool for cancer diagnosis from bone histopathology images,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Deep learning based automated tool for cancer diagnosis from bone histopathology images,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:31.667901Z
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 607eb0a8-c81d-48e1-b039-f98ad4f24e30 · outbound
This paper cites Learning transferable visual models from natural language supervision,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Learning transferable visual models from natural language supervision,
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:33:30.270282Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ee275f95-8aa9-4d7e-b00b-681f07817a89 · outbound
This paper cites Scaling up visual and vision-language representation learning with noisy text supervision,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Scaling up visual and vision-language representation learning with noisy text supervision,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:31.419876Z
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 7e7efc94-99f7-4668-a3d9-6da660f9480b · outbound
This paper cites Contrastive learning of medical visual representations from paired images and text,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Contrastive learning of medical visual representations from paired images and text,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:31.202587Z
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 202a98ee-7cd9-4713-8092-526015c0b6b6 · outbound
This paper cites Towards a Visual-Language Foundation Model for Computational Pathology.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Towards a Visual-Language Foundation Model for Computational Pathology
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:33:30.286198Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b1a387b8-b863-4d74-b773-af88f3f5abf4 · outbound
This paper cites A visual– language foundation model for pathology image analysis using medical twitter,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma A visual– language foundation model for pathology image analysis using medical twitter,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:31.183359Z
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 cd7c7772-da0b-4631-90af-b90d75f45fd0 · outbound
This paper cites Detection of breast cancer from whole slide histopathological images using deep multiple instance cnn,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Detection of breast cancer from whole slide histopathological images using deep multiple instance cnn,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:30.988530Z
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 7108031f-c388-4632-9cbe-ee42eecefaea · outbound
This paper cites Self-learning for weakly supervised gleason grading of local patterns,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Self-learning for weakly supervised gleason grading of local patterns,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:30.903495Z
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 a7e14ba2-59dc-47fc-897b-64486e3a54c3 · outbound
This paper cites An attention-based weakly supervised framework for spitzoid melanocytic lesion diagnosis in whole slide images,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma An attention-based weakly supervised framework for spitzoid melanocytic lesion diagnosis in whole slide images,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:30.782582Z
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 e131413d-5dac-4f5a-a69d-168f021bc6ae · outbound
This paper cites Predicting lymph node metastasis using histopathological images based on multiple instance learning with deep graph convolution,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Predicting lymph node metastasis using histopathological images based on multiple instance learning with deep graph convolution,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:30.735897Z
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 c226f3f2-e8e9-4b44-ae50-c89b3ea7e621 · outbound
This paper cites Classification of volu- metric images using multi-instance learning and extreme value theorem,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Classification of volu- metric images using multi-instance learning and extreme value theorem,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:30.573821Z
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 dad05439-9e02-4444-98ab-db98c496a760 · outbound
This paper cites Attention-based deep multiple instance learning,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Attention-based deep multiple instance learning,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:30.555945Z
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 980ce400-b246-426f-87c4-d43873107587 · outbound
This paper cites Clinical- grade computational pathology using weakly supervised deep learning on whole slide images,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Clinical- grade computational pathology using weakly supervised deep learning on whole slide images,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:30.537968Z
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 edd1f88b-13fa-4c62-9602-6a479a0f4d40 · outbound
This paper cites Transmil: Transformer based correlated multiple instance learning for whole slide image classification,.
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma Transmil: Transformer based correlated multiple instance learning for whole slide image classification,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:33:30.383061Z
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.