Paper Citation Record · LEDGER

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining

As of 14 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2506.07559.

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

pith.paper-citation-record.v1
2506.07559 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:35:36.002297Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

29 of 29 outbound references displayed

verified exact1
verified fuzzy27
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 98e48103-863e-4ccf-92bf-be274e54e690 · outbound

This paper cites Interaction-matrix based personalized image aesthetics assessment,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Interaction-matrix based personalized image aesthetics assessment,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.527519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5a2b6fff-8db7-40d6-9cb4-d1f8c227bda2 · outbound

This paper cites Cross- image region mining with region prototypical network for weakly supervised segmentation,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Cross- image region mining with region prototypical network for weakly supervised segmentation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.508971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3eff5cfc-69cf-40d7-8496-fad7d4cee39d · outbound

This paper cites Decoding bilingual eeg signals with complex semantics using adaptive graph attention convolutional network,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Decoding bilingual eeg signals with complex semantics using adaptive graph attention convolutional network,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.492971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 82fe40d1-44fc-4cfb-bf43-1c73f7be63ee · outbound

This paper cites Few-shot segmentation with optimal transport matching and message flow,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Few-shot segmentation with optimal transport matching and message flow,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.475008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 086fb08b-cec5-4d3c-99ce-2b8a11147e2a · outbound

This paper cites Deep learning- enabled realistic virtual histology with ultraviolet photoacoustic remote sensing microscopy,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Deep learning- enabled realistic virtual histology with ultraviolet photoacoustic remote sensing microscopy,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.458077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bf6785fb-c9f0-4ba3-bcab-37a6b53f4c96 · outbound

This paper cites Virtual staining for histology by deep learning,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Virtual staining for histology by deep learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.441416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9207c80b-53f3-4ffe-b48b-f79f8f6d0b53 · outbound

This paper cites Virtual immunohistochemistry staining for histological images assisted by weakly-supervised learning,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Virtual immunohistochemistry staining for histological images assisted by weakly-supervised learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.426002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 69a36c1f-c486-406e-b20d-58ff3a20d117 · outbound

This paper cites Weakly supervised segmentation with maximum bipartite graph matching,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Weakly supervised segmentation with maximum bipartite graph matching,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.410470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation de961b85-a07e-4245-a42b-1592a563eedd · outbound

This paper cites Learning causality-inspired representation consistency for video anomaly detec- tion,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Learning causality-inspired representation consistency for video anomaly detec- tion,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.394503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d72419a3-c581-4c72-9d08-f6158dd5a961 · outbound

This paper cites A novel cell contour-based instance segmentation model and its ap- plications in her2 breast cancer discrimination,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining A novel cell contour-based instance segmentation model and its ap- plications in her2 breast cancer discrimination,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.377802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 72b582fc-16c0-41c6-9638-1f0088c3c7e5 · outbound

This paper cites Deep learning-enabled virtual histological staining of biological samples,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Deep learning-enabled virtual histological staining of biological samples,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.360013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b7dd234c-6b23-4f2d-a877-d6deb77663a8 · outbound

This paper cites Her2 status in breast cancer: changes in guidelines and complicating factors for interpretation,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Her2 status in breast cancer: changes in guidelines and complicating factors for interpretation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.340088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 82f38b88-9f91-4e39-bb14-d253cf6e5e3e · outbound

This paper cites Ex- ploiting supervision information in weakly paired images for ihc virtual staining,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Ex- ploiting supervision information in weakly paired images for ihc virtual staining,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.322598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 47cbb05d-371c-414c-aa8b-9ccb393fbcce · outbound

This paper cites Pathological semantics-preserving learning for h&e-to- ihc virtual staining,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Pathological semantics-preserving learning for h&e-to- ihc virtual staining,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.301545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b29e157c-3c0b-4781-a88d-1eb422bdbb06 · outbound

This paper cites Efficient supervised pretraining of swin- transformer for virtual staining of microscopy images,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Efficient supervised pretraining of swin- transformer for virtual staining of microscopy images,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.283858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e2e6b35a-79a6-4b76-803d-1c9c00c8460b · outbound

This paper cites A whole-slide foundation model for digital pathology from real-world data,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining A whole-slide foundation model for digital pathology from real-world data,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.266986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1be80d4c-e078-4f0a-a435-176747a88982 · outbound

This paper cites Stephanie: Step-by-Step Dialogues for Mimicking Human Interactions in Social Conversations.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Stephanie: Step-by-Step Dialogues for Mimicking Human Interactions in Social Conversations

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:35:36.048301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2c6a8547-3da4-4770-ac59-c00b2f928212 · outbound

This paper cites Generalized video anomaly event detection: Systematic taxonomy and comparison of deep models,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Generalized video anomaly event detection: Systematic taxonomy and comparison of deep models,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.249454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3951259b-9c4d-45be-bb0a-d7fb71e3adaa · outbound

This paper cites Deepdof-se: affordable deep-learning microscopy platform for slide-free histology,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Deepdof-se: affordable deep-learning microscopy platform for slide-free histology,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.233049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 959813cb-e296-493a-9c3e-f532c7cb6799 · outbound

This paper cites Instant diagnosis of gastroscopic biopsy via deep-learned single-shot femtosecond stimulated raman histology,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Instant diagnosis of gastroscopic biopsy via deep-learned single-shot femtosecond stimulated raman histology,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.215284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8f484a2a-72de-4b09-8dea-3e3a34a64f10 · outbound

This paper cites Generative adversarial networks in digital histopathology: current applications, limitations, ethical considerations, and future directions,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Generative adversarial networks in digital histopathology: current applications, limitations, ethical considerations, and future directions,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.197644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 796977eb-e820-436f-95e6-172875a4be8c · outbound

This paper cites Amp-net: Appearance- motion prototype network assisted automatic video anomaly detection system,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Amp-net: Appearance- motion prototype network assisted automatic video anomaly detection system,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.178966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 658b05d8-0dbd-4754-8ffb-6fb6bc213d1c · outbound

This paper cites Dsff-gan: A novel stain transfer network for generating immunohistochemical image of endometrial cancer,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Dsff-gan: A novel stain transfer network for generating immunohistochemical image of endometrial cancer,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.159931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a888336e-cd1c-4f9b-beac-4d5d0bac65e2 · outbound

This paper cites Staindiff: Transfer stain styles of his- tology images with denoising diffusion probabilistic models and self- ensemble,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Staindiff: Transfer stain styles of his- tology images with denoising diffusion probabilistic models and self- ensemble,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.143900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 710e3409-ebfa-4aa6-bacb-62be133b8ab1 · outbound

This paper cites Pix2pix-based stain-to-stain translation: A solution for robust stain normalization in histopathology images analysis,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Pix2pix-based stain-to-stain translation: A solution for robust stain normalization in histopathology images analysis,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.127800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0d41db23-216e-458a-ae57-4c04085ef4cb · outbound

This paper cites Bci: Breast cancer immunohistochemical image generation through pyramid pix2pix,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Bci: Breast cancer immunohistochemical image generation through pyramid pix2pix,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.111619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 82640b72-2ac1-454f-8c33-57f23fc72c79 · outbound

This paper cites Adaptive supervised patchnce loss for learning h&e-to-ihc stain translation with inconsistent groundtruth image pairs,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Adaptive supervised patchnce loss for learning h&e-to-ihc stain translation with inconsistent groundtruth image pairs,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.095151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1585e037-13c0-40c8-9ead-8987b08af5bf · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Gans trained by a two time-scale update rule converge to a local nash equilibrium,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T05:35:35.997026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58faf4a0-8f8d-486b-b321-a94a248a3ef5 · outbound

This paper cites Con- trastive learning for unpaired image-to-image translation,.

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining Con- trastive learning for unpaired image-to-image translation,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:35:36.065813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.