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Paper Citation Record · LEDGER

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation

As of 23 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2502.09662.

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

pith.paper-citation-record.v1
2502.09662 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:54:57.687678Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

62 of 62 outbound references displayed

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  • verified fuzzy46
  • unresolved14
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a7637794-b1c2-41f6-8693-8bff4042f6a5 · outbound

This paper cites Cancer statistics,.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Cancer statistics,

Reference 1

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Source-reported events for the cited work

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Observation f31452da-6e1c-4d49-8be9-189d61343d14 · outbound

This paper cites Cancer statistics, 2023.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Cancer statistics, 2023

Reference 2

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 4dc24a41-2586-4d76-a2af-3957a389e72e · outbound

This paper cites Cervical cancer.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Cervical cancer

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 04105a40-7171-401c-8b60-f24127592fba · outbound

This paper cites Cervical cancer kills 300,000 people a year—here’s how to speed up its elimination.Nature, 626(7997):30–32, 2024.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Cervical cancer kills 300,000 people a year—here’s how to speed up its elimination.Nature, 626(7997):30–32, 2024

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 16cce2aa-9de8-4b2c-bd36-0ae46a33d48b · outbound

This paper cites Global strategy to accelerate the elimination of cervical cancer as a public health problem.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Global strategy to accelerate the elimination of cervical cancer as a public health problem

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 41a982fd-9812-495e-979d-69bf030944e8 · outbound

This paper cites Cervical cancer prognosis and survival rates.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Cervical cancer prognosis and survival rates

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 600a982e-a5a7-4b14-808c-960efcb574c5 · outbound

This paper cites “smart” cytology: The next generation cytology for precision diagnosis.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation “smart” cytology: The next generation cytology for precision diagnosis

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.552844Z digest=sha256:f9ba2795f42d4e6a3da8d1a43f2ddc602c6be2224657e7e9e030f581eb69de43

Observation e01e5d91-480f-4c3f-9063-32b072ff75be · outbound

This paper cites Discrepancy between cytology and histology in cervical cancer screening: a mul- ticenter retrospective study (kgog 1040).

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Discrepancy between cytology and histology in cervical cancer screening: a mul- ticenter retrospective study (kgog 1040)

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.555507Z digest=sha256:bd3610e6352c91580e8b1d334422482a345ef9329b97164edf254d6e94a5bc43

Observation 31ae3629-2ca0-44ba-a8af-f07b0be33930 · outbound

This paper cites The Bethesda system for reporting cervical cytology: definitions, criteria, and explanatory notes.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation The Bethesda system for reporting cervical cytology: definitions, criteria, and explanatory notes

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation c41f1cfb-8e13-4be2-9d4b-5c09138ce68f · outbound

This paper cites Sipakmed: A new dataset for feature and image based classification of normal and pathological cervical cells in pap smear images.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Sipakmed: A new dataset for feature and image based classification of normal and pathological cervical cells in pap smear images

Reference 10

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.560370Z digest=sha256:2f537b5fd16363887accf38997ff2bd6f0735d58e2021c37c7dd9beb9bb9d23f

Observation ea5d8cd1-365e-47a7-bed9-7fa9c7ff98f5 · outbound

This paper cites Dual-path network with synergistic grouping loss and evidence driven risk stratification for whole slide cervical image analysis.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Dual-path network with synergistic grouping loss and evidence driven risk stratification for whole slide cervical image analysis

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.562877Z digest=sha256:eb43179b5dd893f3930878e52ddf2f7fcad703ee8ee3e1de8907760cd7bbc71c

Observation 84927c84-7e04-4ba0-a8a7-abd9f931779b · outbound

This paper cites Deep learning for computational cytology: A survey.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Deep learning for computational cytology: A survey

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.565390Z digest=sha256:48be30e70be2b81d7c55cf0a05ec249120fbd8aea34f4bdc46249133b4a3ff43

Observation ea7566ee-0f28-473a-b6f4-ac16aa06dec8 · outbound

This paper cites Pap-smear benchmark data for pattern classification.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Pap-smear benchmark data for pattern classification

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 1f5b0067-4a91-4066-ad25-02cb27982472 · outbound

This paper cites A New Cervical Cytology Dataset for Nucleus Detection and Image Classification (Cervix93) and Methods for Cervical Nucleus Detection.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation A New Cervical Cytology Dataset for Nucleus Detection and Image Classification (Cervix93) and Methods for Cervical Nucleus Detection

Reference 14

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:54:57.570218Z digest=sha256:98e81955f022050c6c1713a921b7ab226246ba446c8d7ffe803014c45a5adb70

Observation 38b57949-0c62-42a9-8dd7-679770334e82 · outbound

This paper cites An improved joint optimiza- tion of multiple level set functions for the segmentation of overlapping cervical cells.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation An improved joint optimiza- tion of multiple level set functions for the segmentation of overlapping cervical cells

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:58.037290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.573103Z digest=sha256:44a2e78d729ce6f2177659b76897da372b343328466f5a001093bfe6491445d6

Observation 633c2511-25dc-43ff-bbbe-d4fe2fb4ad9d · outbound

This paper cites Donet: Deep de-overlapping network for cytology instance segmentation.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Donet: Deep de-overlapping network for cytology instance segmentation

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.575535Z digest=sha256:1a7f3f1298f09d946cd49ef8137871a4af7448228668af64e02898a2d5757dca

Observation 9cd37484-8efd-4474-a500-6137c9dc71e6 · outbound

This paper cites Gains: Gradient anomaly-aware biomedical instance segmenta- tion.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Gains: Gradient anomaly-aware biomedical instance segmenta- tion

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.577862Z digest=sha256:390b2db93b6ad69641ec05139ccc089169ed80a8b06b46831b1401582e931fbf

Observation 5a1ffe7c-4340-4f83-a97e-6a5564f1e81a · outbound

This paper cites Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 302ae56a-cbff-4043-be91-1944ae71a174 · outbound

This paper cites A systematic review of deep learning-based cervical cytol- ogy screening: from cell identification to whole slide image analysis.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation A systematic review of deep learning-based cervical cytol- ogy screening: from cell identification to whole slide image analysis

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 48a9554b-5e67-4774-94d1-ecc61d8f6125 · outbound

This paper cites Robust whole slide image analysis for cervical cancer screening using deep learning.Nature communications, 12(1):5639, 2021.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Robust whole slide image analysis for cervical cancer screening using deep learning.Nature communications, 12(1):5639, 2021

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.585364Z digest=sha256:56b5096cc4a687f38084573190afe61eb09724e445cc2380dbbbe4d456e1df7c

Observation 32ee0b7d-c71e-4b28-9bfc-0970ab515d62 · outbound

This paper cites Artificial intelligence enables precision 24 diagnosis of cervical cytology grades and cervical cancer.Nature Communications, 15(1):4369, 2024.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Artificial intelligence enables precision 24 diagnosis of cervical cytology grades and cervical cancer.Nature Communications, 15(1):4369, 2024

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 81e7a806-c4f8-4a83-bb49-314919954f23 · outbound

This paper cites Hybrid ai-assistive diagnostic model permits rapid tbs classification of cervical liquid-based thin-layer cell smears.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Hybrid ai-assistive diagnostic model permits rapid tbs classification of cervical liquid-based thin-layer cell smears

Reference 22

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 9ded9f74-1143-403b-ade1-dd666a5628c6 · outbound

This paper cites Ai-driven cervical cancer cytolog- ical diagnosis solution based on large scale data collections and annotations: A multi-centre clinical validation.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Ai-driven cervical cancer cytolog- ical diagnosis solution based on large scale data collections and annotations: A multi-centre clinical validation

Reference 23

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 92a45d66-f738-4e01-9586-c5c428ce13fa · outbound

This paper cites Towards a general-purpose foundation model for computational pathology.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Towards a general-purpose foundation model for computational pathology

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8a23b808-3c98-4700-83b7-ea50c1dd0c51 · outbound

This paper cites Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation

Reference 25

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation dd0fb639-3576-4ba3-89e1-eba4e4f6ce01 · outbound

This paper cites Dinov2: Learning robust visual features without supervision.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Dinov2: Learning robust visual features without supervision

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 3694ff92-3b58-47d9-9439-8e6c40ca4ceb · outbound

This paper cites Holis- tic and historical instance comparison for cervical cell detection.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Holis- tic and historical instance comparison for cervical cell detection

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation bd9f9390-9d7a-4aa0-a2c4-368b457cf83e · outbound

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

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation An empirical study of training self- supervised vision transformers

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.951727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.605185Z digest=sha256:2748169a7085e34d6ad0c8e161d3a54b85d6832e395a435279cc1beb3c2a35a3

Observation 22fa81cc-5288-4f88-98be-b6202a8febf2 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 29

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unresolved
no resolver link, observed 2026-08-08T05:54:57.607713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f6b25cb8-cf23-4b82-ad50-f4a1ed19d620 · outbound

This paper cites An Efficient Cervical Whole Slide Image Analysis Framework Based on Multi-scale Semantic and Location Deep Features.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation An Efficient Cervical Whole Slide Image Analysis Framework Based on Multi-scale Semantic and Location Deep Features

Reference 30

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verified exact
local_arxiv, observed 2026-08-08T05:54:57.742060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation ff022af9-acef-4a3f-933c-2d64fb6c0eb5 · outbound

This paper cites End-to-end object detection with transformers.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation End-to-end object detection with transformers

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-08T05:54:57.613029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:54:57.613029Z digest=sha256:d4cfbdbe692ab9193a4cbff5af8fc1371a40e18be4a514c1acddf1bb4eae8f8d

Observation a7757c62-0b28-4a3c-a5eb-afba52962bea · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-08T05:54:57.615396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:54:57.615396Z digest=sha256:0a4e7c8636aba59e65cae01a8d2795b47ab4d4cfb72ad790ad5842c4c159988b

Observation 730e36ac-7809-49a4-a6f8-27981717e260 · outbound

This paper cites atypical.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation atypical

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.935357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.618252Z digest=sha256:093e6f4ad821bc6568804dc6430c1cb9f0591639a539fa6a498f32f34f76425d

Observation a8e26c99-4967-4be6-9500-a33d8f6cea62 · outbound

This paper cites Attention-based deep mul- tiple instance learning.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Attention-based deep mul- tiple instance learning

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.928263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.620731Z digest=sha256:fca3ecd5a12e3329e487a63e0251f91f670e11c085d1250431d1a11e044f1195

Observation 2355d0f3-d3cc-4546-af82-3f8d2aa669bf · outbound

This paper cites Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learn- ing.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learn- ing

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.921090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.623245Z digest=sha256:a73d525267917967e726ba4bf5dde594f0d954dcac1b74869c3470781c099a27

Observation dbe5541a-313f-480e-a21e-5f893619aa8c · outbound

This paper cites Transmil: Transformer based correlated multiple instance learning for whole slide image classification.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Transmil: Transformer based correlated multiple instance learning for whole slide image classification

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.913574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.625789Z digest=sha256:7ea52956fc0fb427a05905e9bbebefc6d1bde19164c52bb3899790594fe5ee90

Observation 326814f2-d107-4ab2-b481-6b06fff5d989 · outbound

This paper cites Data-efficient and weakly supervised computational pathology on whole-slide images.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Data-efficient and weakly supervised computational pathology on whole-slide images

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.906248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.628076Z digest=sha256:09564adaee1e5301857a596ededfe7285dde2d010210381a3676cc9376b214ff

Observation 05d9b846-f6b7-49b9-93c2-c008acfa6e4d · outbound

This paper cites Structured state space models for multiple instance learning in digital pathology.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Structured state space models for multiple instance learning in digital pathology

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.898359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.630498Z digest=sha256:7fe2924de26c6fa0da315d518268dbc8a41116f9998e9d205fe0b296dab38396

Observation 611df8fe-33b9-4b2d-86c0-c5db8261f8a8 · outbound

This paper cites Predicting tumour origin with cytology-based deep learning: hype or hope? Nature Reviews Clinical Oncology, pages 1–2, 2024.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Predicting tumour origin with cytology-based deep learning: hype or hope? Nature Reviews Clinical Oncology, pages 1–2, 2024

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.890936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.632922Z digest=sha256:8ec18ce18dcefa0db76e484bea0fa6adeeb6229c6b5aac5c9652d6557bd160f0

Observation 31f0e221-b835-463b-a461-781526dd4c82 · outbound

This paper cites A new paradigm for cytology- based artificial intelligence-assisted prediction for cancers of unknown primary origins.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation A new paradigm for cytology- based artificial intelligence-assisted prediction for cancers of unknown primary origins

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.883432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.635210Z digest=sha256:ed2f1153d38cf3ade6e20126c77ae0768152655a5f843963dc4f43e03b52551f

Observation e31bfaf4-7817-4cee-9328-f2d3dcbbf241 · outbound

This paper cites an unresolved cited work.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-08T05:54:57.875721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.637596Z digest=sha256:4408621320e1c6355e9b3ef9f0095dd03b045d362e276a8ad02631655355c08a

Observation 67a2d409-a9e2-4099-a6a8-3b2e72e4e72f · outbound

This paper cites A foundation model for clinical-grade computational pathology and rare cancers detection.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation A foundation model for clinical-grade computational pathology and rare cancers detection

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.868264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.639986Z digest=sha256:54912d8c1e9f1df6741548cb019c56698154caaa10e36bc6089b2f69c747d10d

Observation 672c51d1-9fc6-4f4e-98e3-4053e4e70f8b · outbound

This paper cites A visual-language foundation model for computational pathology.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation A visual-language foundation model for computational pathology

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-08T05:54:57.642459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:54:57.642459Z digest=sha256:143be7e1444db7c394eb515b653a8e08f0698b5e02002d282cd81b8cd9a223d6

Observation d480f0e4-64f3-40ed-9f6f-5b358523091e · outbound

This paper cites The cancer genome atlas pan-cancer analysis project.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation The cancer genome atlas pan-cancer analysis project

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.856449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.644883Z digest=sha256:f836870ac60693bd5f9312d1c580fd12a60dfcbfdd5e840a46ddc1d2caee027b

Observation 34b188f0-1451-4984-a66b-66469df682eb · outbound

This paper cites Deep learning models for thyroid nodules diagnosis of fine-needle aspiration biopsy: a retrospective, prospective, multicentre study in china.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Deep learning models for thyroid nodules diagnosis of fine-needle aspiration biopsy: a retrospective, prospective, multicentre study in china

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.849102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.647177Z digest=sha256:b0022df1cd47ca4d7b926b7938ce1666cd72bdce8c3a6bb9e47614505a52cc58

Observation ddf9d579-604d-40be-b5af-fc57729467db · outbound

This paper cites Cytol- ogy assessment can predict survival for patients with metastatic pancreatic neuroendocrine neoplasms.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Cytol- ogy assessment can predict survival for patients with metastatic pancreatic neuroendocrine neoplasms

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.841801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.649583Z digest=sha256:0465ad171b837a55e3408f23f4fb1d527547cdd57af4a4ec1b577f18a7ef9872

Observation 5cf88cd5-e043-4067-910a-25580dd56aed · outbound

This paper cites Gas- tric cancer with positive peritoneal cytology: survival benefit after induction chemotherapy and conversion to negative peritoneal cytology.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Gas- tric cancer with positive peritoneal cytology: survival benefit after induction chemotherapy and conversion to negative peritoneal cytology

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.834757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.652124Z digest=sha256:8e9e7b39976268d1b65330f25880614d5d57efc4736163acb46d2880732130fa

Observation d06ae80c-52cb-41a7-b40d-e12485fde122 · outbound

This paper cites Current role of cytopathology in the molecular and computational era: The perspective of young pathologists.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Current role of cytopathology in the molecular and computational era: The perspective of young pathologists

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.827629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.654502Z digest=sha256:034fe92bfc8bc9e914102740d9e57b55777e76eda962feef54046828b82bc0f9

Observation 143ba15e-96f1-4197-a3c4-9e936aa01134 · outbound

This paper cites an unresolved cited work.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-08T05:54:57.820243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.656983Z digest=sha256:2a24d954fab09796eb0acf6f11b5d2086bcb69b1853b604126f271ab3fc49203

Observation c230f118-56d9-4353-9406-67d59a3b2a83 · outbound

This paper cites Openslide: A vendor-neutral software foundation for digital pathology.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Openslide: A vendor-neutral software foundation for digital pathology

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.812864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.659460Z digest=sha256:352be1497339a0ae5bfe6262c0bef359fbebbb83a90b853cf62b9b8e51777118

Observation 9d0ac0a8-8f98-4e65-933b-5fc00cf51042 · outbound

This paper cites A visual–language foundation model for pathology image analysis using medical twitter.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation A visual–language foundation model for pathology image analysis using medical twitter

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.805707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.661971Z digest=sha256:e53f12ff672e8597a9e94f46849d6ef8b0f6724120bd9c07c2ecda2938af815c

Observation 392b9067-c6f3-42d1-8342-bda40dcb7c6b · outbound

This paper cites Transformer-based unsupervised contrastive learning for histopathological image classification.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Transformer-based unsupervised contrastive learning for histopathological image classification

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.798609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.664365Z digest=sha256:72eb6af01bfa7d7623487d3faa6108a22e495b8b2826a110b57495182835367b

Observation 8867328c-db86-4b07-ad5a-979191a5b2ab · outbound

This paper cites Less: Label-efficient multi-scale learning for cytological whole slide image screening.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Less: Label-efficient multi-scale learning for cytological whole slide image screening

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.791353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.666784Z digest=sha256:fc930d24e4cd9a8ec2738373febf7902bfd8b4083cf31a9abfd0bfaa52c3bff2

Observation d5c39534-ba62-4605-9a06-2505930ac437 · outbound

This paper cites Hmil: Hier- archical multi-instance learning for fine-grained whole slide image classification.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Hmil: Hier- archical multi-instance learning for fine-grained whole slide image classification

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.783830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.669471Z digest=sha256:6fb937a4c3c3434106b19b911700e724796dd8aec53deedaf2b2131ad7f41a68

Observation c6fb5448-02d0-4c3b-b4ec-770294df8386 · outbound

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

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-08T05:54:57.671964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:54:57.671964Z digest=sha256:a29da85565a10230f75a788ddaf1faef0474ce518fbf911e4ea13d4cd1a82a7d

Observation dd5d965e-41d1-489a-a872-1d85f0a7f120 · outbound

This paper cites YOLOv3: An Incremental Improvement.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation YOLOv3: An Incremental Improvement

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-08T05:54:57.674656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:54:57.674656Z digest=sha256:81377afb371517bcaced552ddfa88abfb8739c0675f261080617bd158ce626fc

Observation 053eeb1f-aa36-4ea1-b939-10e8de3506b8 · outbound

This paper cites Focal loss for dense object detection.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Focal loss for dense object detection

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-08T05:54:57.677401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:54:57.677401Z digest=sha256:33e2759ab25ccbd255a4b090acc731f5ac241ab029d71c3610a41d6282f908ba

Observation 430d4efa-f38d-4fca-bb78-17b8ae5e9105 · outbound

This paper cites Dataset shift in machine learning.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Dataset shift in machine learning

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.772832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.679778Z digest=sha256:2b46d2c92ca1c4d74d4ef2bd992a8455dbf5c9d0646d982e3075b1139db45126

Observation 6f5932c0-799b-4212-87da-9e1c553e70ca · outbound

This paper cites Towards Launching AI Algorithms for Cellular Pathology into Clinical & Pharmaceutical Orbits.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Towards Launching AI Algorithms for Cellular Pathology into Clinical & Pharmaceutical Orbits

Reference 59

Resolution
verified exact
local_arxiv, observed 2026-08-08T05:54:57.713180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.682228Z digest=sha256:6e256b9b74f1260f461a88a8f76ec8fc0b4b71fd6dcaea2fb26b959deaa7c51b

Observation 48f2018d-e918-412a-94d2-c9d66467c108 · outbound

This paper cites Continual test-time domain adaptation.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Continual test-time domain adaptation

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-08T05:54:57.685215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:54:57.685215Z digest=sha256:e2b0c2cd4261c22a1ffdfd5aaf23d6b3e01403a92ceced79dc14e55905b053a1

Observation 23af4f97-e7c2-4368-ba75-5285621dabad · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Pytorch: An imperative style, high-performance deep learning library

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:54:57.761805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.687678Z digest=sha256:27eef02b6cb3fc112e130a3d8b29cdc749a8c760156430d7603e0c5d0e5badde

Observation 64dd485d-fffd-43b4-80db-ff87779cc859 · outbound

This paper cites an unresolved cited work.

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation Unresolved cited work

Reference 2024

Resolution
unresolved
raw_fallback, observed 2026-08-08T05:54:58.128921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-08T05:54:57.536943Z digest=sha256:09e860a77dec9f4f81931c6a5214693ff735f1ec88b749641801c1ef7947d515

Pith citing papers

No inbound Pith citation observations are available.