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Paper Citation Record · LEDGER

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification

As of 9 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2508.20745.

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

pith.paper-citation-record.v1
2508.20745 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:54:46.972819Z

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

11 of 11 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a49194f2-260f-4299-97af-13d60ad4399d · outbound

This paper cites Domain generalization across tumor types, laboratories, and species—insights from the 2022 edition of the mitosis domain generalization challenge.

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification Domain generalization across tumor types, laboratories, and species—insights from the 2022 edition of the mitosis domain generalization challenge

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:54:47.116459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T14:54:46.932992Z digest=sha256:557579f14aeebe090a3b932c1ee00b750c74a9397de020fc0d133adfc8e2d740

Observation 37891808-142c-4e39-8bb4-e7f171a43481 · outbound

This paper cites Domain Generalization with MixStyle.

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification Domain Generalization with MixStyle

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T14:54:46.937102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:54:46.937102Z digest=sha256:03edc6437fd49f101d548041e7eeb036c053d621d74e8778967fad021752cbb6

Observation cbdd68ca-2389-4f33-97df-1cc2b39439db · outbound

This paper cites Cbam: Convolutional block attention module.

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification Cbam: Convolutional block attention module

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:54:47.104292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T14:54:46.941265Z digest=sha256:48071d36c4e3be7f8328fbde7b9c8db5a0c16849e767505764e37c056d8a94d0

Observation e114158f-d3a4-400e-8346-196687e0791e · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification Distilling the Knowledge in a Neural Network

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T14:54:46.945172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:54:46.945172Z digest=sha256:125793a0d9670014caac7ff5e26ab69317d614dfe36514bc070eb6524e1294a2

Observation 6a4dc928-433f-43bc-bcfd-4202794e79a2 · outbound

This paper cites Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results.

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:54:47.092475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T14:54:46.949726Z digest=sha256:ff7b50fc35ef0dc043064a464a204147361c0f09cc1ee531061d7aafef1a70b6

Observation 038d4e64-2a50-4fbe-a358-bce6dce2ba2f · outbound

This paper cites A dataset of atypical vs normal mitoses classification for midog - 2025, April 2025.

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification A dataset of atypical vs normal mitoses classification for midog - 2025, April 2025

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-05T14:54:46.953664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:54:46.953664Z digest=sha256:c69f20a78c2184dd91c920acf3af0a9850c9fac89604d18ce96e04c48dc954d5

Observation 129cf607-f5bc-4ac5-9197-fefd8302d329 · outbound

This paper cites Histologic dataset of normal and atypical mitotic figures on human breast cancer (ami-br).

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification Histologic dataset of normal and atypical mitotic figures on human breast cancer (ami-br)

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T14:54:46.958151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:54:46.958151Z digest=sha256:571a93dc85ad6856232b88ea6a0d007aeab56283dbda88ef72ff8c6142724fcc

Observation a0547a1f-ce15-45ac-9ee2-816a71235b58 · outbound

This paper cites Hawkins, Adrienne M.

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification Hawkins, Adrienne M

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:54:47.064431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T14:54:46.961786Z digest=sha256:7b3a5f44cbe12605f6b6b0557d72ec780fbb5782de94fb6742dda6b78b4e6c8a

Observation d9321eda-75fd-4f65-8221-bfc8c91e52ab · outbound

This paper cites Densely connected convolutional networks.

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification Densely connected convolutional networks

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:54:47.052826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T14:54:46.965205Z digest=sha256:2e359be827671ca6d7163067feefdf09618ad72634d659321f3ea9dfc63e9e23

Observation cb85294c-2488-493a-9a83-5fb23d760bf2 · outbound

This paper cites Domain-adversarial training of neural networks.

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification Domain-adversarial training of neural networks

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:54:47.040922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T14:54:46.969083Z digest=sha256:58a60dcc8a473ce5579653b96eadf9e686d95c5cf6b7743f792fdcbc997a92de

Observation 9aefbd59-489c-4b2e-a3cb-71b33912167e · outbound

This paper cites write newline.

Mix, Align, Distil: Reliable Cross-Domain Atypical Mitosis Classification write newline

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-05T14:54:46.972819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:54:46.972819Z digest=sha256:7f35efa23e67e256cb80176947c301d3710b7afeed13d736ecdd7a54dff994bf

Pith citing papers

No inbound Pith citation observations are available.