Pith. sign in

Paper Citation Record · LEDGER

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification

As of 9 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2502.08200.

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

pith.paper-citation-record.v1
2502.08200 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:06:34.120531Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T18:27:47.338007Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T23:07:27.007771Z

Reference resolution

15 of 15 outbound references displayed

  • verified exact0
  • verified fuzzy10
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 49de2bcb-b1db-4bbe-a8b7-d596920d3725 · outbound

This paper cites Identity mappings in deep residual networks,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification Identity mappings in deep residual networks,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:06:34.501633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T10:06:34.007371Z digest=sha256:48bc79adbb08ae7095157ecec8f4246f71d005b6c40db04de7524e09102cc215

Observation c981fe1b-36c3-4e78-8523-17b03d1c2a3f · outbound

This paper cites Some methods for classification and analysis of multivariate observations,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification Some methods for classification and analysis of multivariate observations,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:06:34.477333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T10:06:34.015471Z digest=sha256:57a88fe32977fb88c0ced4a71807446ab492f386eb1c0cc255c2b9bcbe343e51

Observation f8a7147d-8563-48ac-b6db-984bb0055ff0 · outbound

This paper cites A neural-network-based approach to white blood cell classification,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification A neural-network-based approach to white blood cell classification,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:06:34.455968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T10:06:34.022235Z digest=sha256:ed53728713555cd92844791ca56ad01e79b873ac23b4f6424d5c887eb4a51108

Observation 54f0a7b8-a360-4bad-ba08-849084378beb · outbound

This paper cites Computer aided system for red blood cell classification in blood smear image,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification Computer aided system for red blood cell classification in blood smear image,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:06:34.432956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T10:06:34.028085Z digest=sha256:9bdd28cf28bbe5ba3366157bbeb9031ee01d1136886b7ac09e6d3bb177ab3f3f

Observation aed639a8-f8e8-4a35-89dd-2a2556e794ff · outbound

This paper cites Fusing pre-trained convolutional neural net- works features for multi-differentiated subtypes of liver cancer on histopathological images,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification Fusing pre-trained convolutional neural net- works features for multi-differentiated subtypes of liver cancer on histopathological images,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:06:34.412881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T10:06:34.034449Z digest=sha256:8bcda29d1e9b68818c802d7e6fb051e0dd86e43269155c2911e08af9a17b5630

Observation a846d49b-1869-4e4c-b337-7c5cb148d678 · outbound

This paper cites Ultrasound nodule segmentation using asymmetric learning with simple clinical annotation,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification Ultrasound nodule segmentation using asymmetric learning with simple clinical annotation,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:06:34.389995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T10:06:34.040972Z digest=sha256:21f80ff5f42d21d851363879a59381fa356b29bac6c09038d543fd46191e66bc

Observation e9ca00ca-6e21-4ebe-ab2f-cbf800086a1b · outbound

This paper cites Sam- driven weakly supervised nodule segmentation with uncertainty- aware cross teaching,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification Sam- driven weakly supervised nodule segmentation with uncertainty- aware cross teaching,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:06:34.365972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T10:06:34.049884Z digest=sha256:0d35c84dee31cf7d1c0dedc2bd8f31b9a2fc9f2968924870778003ba52e6dfc9

Observation 010fd642-88fb-4a69-9055-af2cb5413506 · outbound

This paper cites HFGS: 4D Gaussian Splatting with Emphasis on Spatial and Temporal High-Frequency Components for Endoscopic Scene Reconstruction.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification HFGS: 4D Gaussian Splatting with Emphasis on Spatial and Temporal High-Frequency Components for Endoscopic Scene Reconstruction

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-08T10:06:34.055414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:06:34.055414Z digest=sha256:8a2486537e3f13955b5bb3972178b3c0111539281f68f2095d5b51b66e62c13b

Observation 85743e6b-5c3e-45ee-8249-32ba0b725b58 · outbound

This paper cites D-lmbmap: a fully automated deep-learning pipeline for whole-brain profiling of neural circuitry,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification D-lmbmap: a fully automated deep-learning pipeline for whole-brain profiling of neural circuitry,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:06:34.338292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T10:06:34.060533Z digest=sha256:322dc1f106a42b9d6cbe451045247c994feefed8704355c91753acfa8fe8e173

Observation 261a7220-5a0b-48ef-97ac-b6029cd7d0fb · outbound

This paper cites An empirical study of training self- supervised vision transformers,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification An empirical study of training self- supervised vision transformers,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:06:34.319497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T10:06:34.067584Z digest=sha256:7d521ffafef2810da863cc87e3dcdccca43eba93a88ca22b3a5022952568e5ca

Observation 7fded294-2c4d-417e-9ce9-ffed97e02e23 · outbound

This paper cites ConvMAE: Masked Convolution Meets Masked Autoencoders.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification ConvMAE: Masked Convolution Meets Masked Autoencoders

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-08T10:06:34.074670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:06:34.074670Z digest=sha256:1d1eb81f29232ea3f3c3a35adf32b4b2c3fb47f0b4fa830b1bcdbe10a6e44169

Observation ed654796-112a-402f-8c1a-4eb4edfe5297 · outbound

This paper cites Mixed autoencoder for self-supervised visual representation learning,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification Mixed autoencoder for self-supervised visual representation learning,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T10:06:34.302012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T10:06:34.091884Z digest=sha256:b41944c207ec40ebc5d92dfe006c7556986a61c1fef14d066a4a031d43ede0ab

Observation fcd13464-3824-4972-a04e-18e0da04e78c · outbound

This paper cites Masked autoencoders are scalable vision learners,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification Masked autoencoders are scalable vision learners,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-08T10:06:34.103137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:06:34.103137Z digest=sha256:e3f86b5477717ab7986a5ff5fca8447b91bb37c5407f4b067ef84ff37b95dbf5

Observation 26497ba8-e85f-4cc5-8642-040e021e74e0 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification Momentum contrast for unsupervised visual representation learning,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-08T10:06:34.113601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:06:34.113601Z digest=sha256:e1c9162106dc7dcfa6e9564c3a39b1a4f84793c5fcb0427dd552ff125e913494

Observation 0b70938e-5dee-4230-b07a-2c03b88d7826 · outbound

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

ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-08T10:06:34.120531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:06:34.120531Z digest=sha256:0d5f8d85435718028699f24400f37104cbd7a48a9d86ba1b13af63586d393e02

Pith citing papers

Observation fbfb599f-ac38-4034-a82c-31938c8aaa09 · inbound

Shift-Dependent Asymmetry: Orthogonal Inverse Low-Rank Adaptation for Federated Medical Segmentation cites this paper.

Shift-Dependent Asymmetry: Orthogonal Inverse Low-Rank Adaptation for Federated Medical Segmentation ActiveSSF: An Active-Learning-Guided Self-Supervised Framework for Long-Tailed Megakaryocyte Classification

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-07-02T23:07:27.009338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T18:27:47.338007Z digest=sha256:50a988d60b2cb873bd5c2ed3a52d23896688d8f73672cece3aa822d9364ed591