Paper Citation Record · LEDGER

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers

As of 13 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 2 inbound Pith citation observations for arXiv:2412.04377.

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

pith.paper-citation-record.v1
2412.04377 v3

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:37:22.384571Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:39:52.190888Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

68 of 68 outbound references displayed

verified exact1
verified fuzzy58
unresolved9
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External citation measurements

1
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation e1109f25-022f-46b2-83ca-41bf232cd896 · outbound

This paper cites Kempton, Petrus C.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Kempton, Petrus C

Reference 1

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Observation 8e89759c-6dc9-4a78-86c8-6d462a88773d · outbound

This paper cites The area above the ordinal dominance graph and the area below the receiver operating character- istic graph.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers The area above the ordinal dominance graph and the area below the receiver operating character- istic graph

Reference 2

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Observation 02f193d2-4b35-4164-aaaa-488cf0644439 · outbound

This paper cites Unachievable region in precision-recall space and its effect on empirical evaluation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Unachievable region in precision-recall space and its effect on empirical evaluation

Reference 3

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Observation a5d8ae2e-04f9-4388-9f2c-8958b8542c54 · outbound

This paper cites Briggs and Russell Zaretzki.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Briggs and Russell Zaretzki

Reference 4

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A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Unresolved cited work

Reference 5

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Observation aacb483c-51e9-4349-bcc6-5ef71db52e4f · outbound

This paper cites COCO- stuff: Thing and stuff classes in context.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers COCO- stuff: Thing and stuff classes in context

Reference 6

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Observation bcf63f50-da3b-4955-8ad2-f7a68a193941 · outbound

This paper cites GCNet: Non-local networks meet squeeze-excitation networks and beyond.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers GCNet: Non-local networks meet squeeze-excitation networks and beyond

Reference 7

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Observation ed088527-402a-49e8-b349-3200dd4baf88 · outbound

This paper cites Carrington, Douglas G.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Carrington, Douglas G

Reference 8

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Observation b6f412c2-8965-4d18-b97b-605dd58c3448 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 9

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Observation 33d23cc6-b3b5-4347-9ef4-5247e1b646a8 · outbound

This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Encoder-decoder with atrous separable convolution for semantic image segmentation

Reference 10

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Observation 57b074e9-f410-48de-a8a6-2877c0dab93f · outbound

This paper cites Schwing, and Alexander Kir- illov.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Schwing, and Alexander Kir- illov

Reference 11

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This paper cites Schwing, Alexan- der Kirillov, and Rohit Girdhar.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Schwing, Alexan- der Kirillov, and Rohit Girdhar

Reference 12

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Observation ac3fd117-70b1-4b37-8540-332df5504f65 · outbound

This paper cites MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark

Reference 13

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This paper cites The cityscapes dataset for semantic urban scene understanding.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers The cityscapes dataset for semantic urban scene understanding

Reference 14

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Observation 2e061afc-a7a2-457c-abe7-ff82347f72ef · outbound

This paper cites The relationship between precision-recall and ROC curves.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers The relationship between precision-recall and ROC curves

Reference 15

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Observation 3729cf35-e6f1-45d0-aad9-ee633aad84fc · outbound

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A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Unresolved cited work

Reference 16

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Observation d722d959-6076-4891-ba11-1f03736ad201 · outbound

This paper cites Rethinking BiSeNet for real-time semantic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Rethinking BiSeNet for real-time semantic segmentation

Reference 17

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Observation 65c2eddf-7f5b-46d5-a362-25a5c9e181d5 · outbound

This paper cites ROC graphs: Notes and practical considera- tions for researchers.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers ROC graphs: Notes and practical considera- tions for researchers

Reference 18

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This paper cites An introduction to ROC analysis.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers An introduction to ROC analysis

Reference 19

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This paper cites The geometry of ROC space: Understanding machine learning metrics through ROC isometrics.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers The geometry of ROC space: Understanding machine learning metrics through ROC isometrics

Reference 20

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Observation 33f65cb8-15b1-447d-a4ae-04586b85ae21 · outbound

This paper cites Dual attention network for scene segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Dual attention network for scene segmentation

Reference 21

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Observation 77965e81-7c5c-40c4-9b1c-b6d0e131f3b8 · outbound

This paper cites Dynamic multi- scale filters for semantic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Dynamic multi- scale filters for semantic segmentation

Reference 22

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Observation 13a7e24c-9545-41ab-a059-6743f99aeff1 · outbound

This paper cites Adaptive pyramid context network for seman- tic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Adaptive pyramid context network for seman- tic segmentation

Reference 23

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Observation dbf24884-0ec1-4305-8476-e4e0a975a27a · outbound

This paper cites Interlaced Sparse Self-Attention for Semantic Segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Interlaced Sparse Self-Attention for Semantic Segmentation

Reference 24

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This paper cites CCNet: Criss-cross attention for semantic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers CCNet: Criss-cross attention for semantic segmentation

Reference 25

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Observation f547c5b6-e6df-4856-a5e8-362618c9f653 · outbound

This paper cites Population and Empirical PR Curves for Assessment of Ranking Algorithms.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Population and Empirical PR Curves for Assessment of Ranking Algorithms

Reference 26

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This paper cites Panoptic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Panoptic segmentation

Reference 27

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This paper cites PointRend: Image segmentation as rendering.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers PointRend: Image segmentation as rendering

Reference 28

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Observation 9ba62669-a465-46b7-a01a-e22935c13953 · outbound

This paper cites Expectation-maximization attention net- works for semantic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Expectation-maximization attention net- works for semantic segmentation

Reference 29

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This paper cites Shah, and Aarti Singh.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Shah, and Aarti Singh

Reference 30

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This paper cites Fully convolutional networks for semantic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Fully convolutional networks for semantic segmentation

Reference 31

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Observation 41843a55-ad4b-4c16-8053-57e6db93ee2c · outbound

This paper cites On the statistical consistency of algo- rithms for binary classification under class imbalance.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers On the statistical consistency of algo- rithms for binary classification under class imbalance

Reference 32

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This paper cites Receiver operating characteristic curve: overview and practical use for clinicians.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Receiver operating characteristic curve: overview and practical use for clinicians

Reference 33

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This paper cites How trustwor- thy are performance evaluations for basic vision tasks?IEEE Trans.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers How trustwor- thy are performance evaluations for basic vision tasks?IEEE Trans

Reference 34

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This paper cites Summa- rizing the performances of a background subtraction algo- rithm measured on several videos.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Summa- rizing the performances of a background subtraction algo- rithm measured on several videos

Reference 35

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This paper cites The Tile: A 2D Map of Ranking Scores for Two-Class Classification.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers The Tile: A 2D Map of Ranking Scores for Two-Class Classification

Reference 36

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This paper cites Foundations of the theory of performance-based ranking.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Foundations of the theory of performance-based ranking

Reference 37

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This paper cites Fast-SCNN: Fast Semantic Segmentation Network.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Fast-SCNN: Fast Semantic Segmentation Network

Reference 38

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This paper cites Evaluation: from precision, re- call and F-measure to ROC, informedness, markedness & correlation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Evaluation: from precision, re- call and F-measure to ROC, informedness, markedness & correlation

Reference 39

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This paper cites Vi- sion transformers for dense prediction.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Vi- sion transformers for dense prediction

Reference 40

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This paper cites Alvarez, Luis M.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Alvarez, Luis M

Reference 41

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Observation 36f4c2f9-d9c5-4b01-bf29-51ce25d2d106 · outbound

This paper cites Fully convolutional networks for semantic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Fully convolutional networks for semantic segmentation

Reference 42

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This paper cites A systematic analysis of performance measures for classification tasks.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers A systematic analysis of performance measures for classification tasks

Reference 43

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This paper cites Segmenter: Transformer for semantic segmenta- tion.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Segmenter: Transformer for semantic segmenta- tion

Reference 44

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This paper cites Classification assessment methods.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Classification assessment methods

Reference 45

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This paper cites Non-local neural networks.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Non-local neural networks

Reference 46

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This paper cites FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation

Reference 47

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This paper cites CGNet: A light-weight context guided network for semantic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers CGNet: A light-weight context guided network for semantic segmentation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:23.345189Z

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Observation 020198d1-2669-4278-8532-88009d772060 · outbound

This paper cites Unified perceptual parsing for scene understand- ing.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Unified perceptual parsing for scene understand- ing

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:23.316540Z

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Observation 9f5ccca4-929e-4cfa-94e7-645f632ed1f3 · outbound

This paper cites Alvarez, and Ping Luo.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Alvarez, and Ping Luo

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:23.281391Z

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Observation fb1d552c-96dd-4362-ad2f-5849d88a91aa · outbound

This paper cites Side adapter network for open-vocabulary seman- tic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Side adapter network for open-vocabulary seman- tic segmentation

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:23.250588Z

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Observation d35a31ab-414f-4992-8844-0ae6cc20b7d6 · outbound

This paper cites Disentangled non-local neural networks.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Disentangled non-local neural networks

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:23.228765Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5d8f2fd0-0d80-49f9-a553-b39ea2404d20 · outbound

This paper cites BiSeNet: Bilateral segmentation network for real-time semantic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers BiSeNet: Bilateral segmentation network for real-time semantic segmentation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:23.156066Z

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Observation f71d7643-fb8b-4a43-97b4-924873684b61 · outbound

This paper cites BiSeNet V2: Bilateral net- work with guided aggregation for real-time semantic seg- mentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers BiSeNet V2: Bilateral net- work with guided aggregation for real-time semantic seg- mentation

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:23.120630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5ae84735-9473-447b-b395-a832035a9e4f · outbound

This paper cites BDD100K: A diverse driving dataset for hetero- geneous multitask learning.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers BDD100K: A diverse driving dataset for hetero- geneous multitask learning

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:23.084796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a20de8b7-eb3a-49d3-8e9c-1d1776bf03d3 · outbound

This paper cites Object- contextual representations for semantic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Object- contextual representations for semantic segmentation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:23.049875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c4904209-a142-486f-b8c5-c12f7ec65bc1 · outbound

This paper cites Con- text encoding for semantic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Con- text encoding for semantic segmentation

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:23.019089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 49503752-fb5f-4748-ab3d-8292697d9a25 · outbound

This paper cites K-Net: Towards unified image segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers K-Net: Towards unified image segmentation

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:22.992045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c0eca277-5bfd-4ea0-acac-9e9aeb0a1115 · outbound

This paper cites Pyramid scene parsing network.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Pyramid scene parsing network

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:22.963999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6f4d8d13-6aa1-4a7b-9453-296b91df9e5d · outbound

This paper cites ICNet for real-time semantic segmenta- tion on high-resolution images.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers ICNet for real-time semantic segmenta- tion on high-resolution images

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:22.938071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e06026e8-c075-4ef8-84d5-f5414e2e599e · outbound

This paper cites PSANet: Point- wise spatial attention network for scene parsing.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers PSANet: Point- wise spatial attention network for scene parsing

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:22.884025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 489294fc-4912-4c1b-b316-c831b67fe95e · outbound

This paper cites Torr, and Li Zhang.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Torr, and Li Zhang

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:22.851254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1c86a819-2a24-4be7-8ffe-66f860e5c95f · outbound

This paper cites Scene parsing through ADE20K dataset.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Scene parsing through ADE20K dataset

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:22.811542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c1563179-1a01-436d-932e-ac95cddd540b · outbound

This paper cites Asymmetric non-local neural networks for semantic segmentation.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Asymmetric non-local neural networks for semantic segmentation

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:22.779743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4dad0600-6f9a-4c8e-b0a4-1162adcd9769 · outbound

This paper cites an unresolved cited work.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-11T21:37:22.739765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c1ef577c-f639-4c48-846f-38bb6490e44b · outbound

This paper cites the harmonic mean) and horizontally with f : x 7→ (1 − x)−1 [36].

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers the harmonic mean) and horizontally with f : x 7→ (1 − x)−1 [36]

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:22.707405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7ef239b3-a6b1-4357-945c-de02651f87f2 · outbound

This paper cites an unresolved cited work.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-11T21:37:22.680412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d9553a69-f4d2-4694-99a2-09dc6b93cee9 · outbound

This paper cites Publ., 2020.

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers Publ., 2020

Reference 207

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:37:23.189623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

Observation b9b43ba5-748c-4cae-a062-abac984c4ad5 · inbound

The Tile: A 2D Map of Ranking Scores for Two-Class Classification cites this paper.

The Tile: A 2D Map of Ranking Scores for Two-Class Classification A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T21:39:52.190888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b2588a3-6366-490e-b51e-fcf5ffb67a75 · inbound

Event Detection in Videos: A Framework for the Development of New Methods cites this paper.

Event Detection in Videos: A Framework for the Development of New Methods A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-07-11T19:48:13.247650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.