Paper Citation Record · LEDGER

Contrastive Order Learning: A General Framework for Ordinal Regression

As of 10 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2607.08109.

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

pith.paper-citation-record.v1
2607.08109 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T12:55:50.017123Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

19 of 19 outbound references displayed

verified exact6
verified fuzzy11
unresolved1
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e5137ff8-a1b0-45f7-b9f0-f73bb56a2040 · outbound

This paper cites An Effectiveness Metric for Ordinal Classification: Formal Properties and Experimental Results.

Contrastive Order Learning: A General Framework for Ordinal Regression An Effectiveness Metric for Ordinal Classification: Formal Properties and Experimental Results

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-10T12:57:07.562790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7ad558ce-37ec-4af4-98d4-219d3e97fdc8 · outbound

This paper cites SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation.

Contrastive Order Learning: A General Framework for Ordinal Regression SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:57:07.709423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 143e0660-97ef-45b8-966e-ece4a826db3a · outbound

This paper cites J., Misevic, D., Steiner, U., and Guyon, I.

Contrastive Order Learning: A General Framework for Ordinal Regression J., Misevic, D., Steiner, U., and Guyon, I

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:57:07.714564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 53606953-da95-4451-b89d-41ed424a5468 · outbound

This paper cites QMamba: On First Exploration of Vision Mamba for Image Quality Assessment.

Contrastive Order Learning: A General Framework for Ordinal Regression QMamba: On First Exploration of Vision Mamba for Image Quality Assessment

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-07-10T12:57:07.544196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ccf3afe2-ab2b-4a31-92b5-4b09c63248eb · outbound

This paper cites Domain Adaptation for Semantic Segmentation via Patch-Wise Contrastive Learning.

Contrastive Order Learning: A General Framework for Ordinal Regression Domain Adaptation for Semantic Segmentation via Patch-Wise Contrastive Learning

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-07-10T12:57:07.553302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8ce06626-c8d6-41b8-aab1-454c8a0d3321 · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

Contrastive Order Learning: A General Framework for Ordinal Regression SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-10T12:57:07.556185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8e918866-615d-4013-968b-2e287b5ec43e · outbound

This paper cites Decoupled Weight Decay Regularization.

Contrastive Order Learning: A General Framework for Ordinal Regression Decoupled Weight Decay Regularization

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-07-10T12:57:07.541101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9c6546ec-6479-45a2-8425-17ff013cc704 · outbound

This paper cites an unresolved cited work.

Contrastive Order Learning: A General Framework for Ordinal Regression Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-07-10T12:57:07.711039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 47e4f8f0-adf1-4469-83d2-2a35c67c7488 · outbound

This paper cites We adopt the evaluation protocol in (Gustafsson et al., 2020; Berg et al., 2021).

Contrastive Order Learning: A General Framework for Ordinal Regression We adopt the evaluation protocol in (Gustafsson et al., 2020; Berg et al., 2021)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:57:07.705788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cd9c598f-c230-4ec5-8dc6-f3c1e5d9151b · outbound

This paper cites For data augmentation, only random horizontal flipping is applied.

Contrastive Order Learning: A General Framework for Ordinal Regression For data augmentation, only random horizontal flipping is applied

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:57:07.707577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fc6da56a-0df3-4527-8336-683d2f3e2afc · outbound

This paper cites Each image is assigned image attribute scores, but we use only the overall image quality scores in the range [0, 100].

Contrastive Order Learning: A General Framework for Ordinal Regression Each image is assigned image attribute scores, but we use only the overall image quality scores in the range [0, 100]

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:57:07.719941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 14e14241-82e1-4948-8199-bd9120c8913a · outbound

This paper cites For data augmentation, we use top-left, bottom-right, and center crops during training and use the average feature of the three cropped images.

Contrastive Order Learning: A General Framework for Ordinal Regression For data augmentation, we use top-left, bottom-right, and center crops during training and use the average feature of the three cropped images

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:57:07.703988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 52fb470d-6d47-4ab5-a03e-6ee126ad7e7e · outbound

This paper cites All videos have a resolution of 540p.

Contrastive Order Learning: A General Framework for Ordinal Regression All videos have a resolution of 540p

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:57:07.712851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0998ef8e-f15f-4235-9382-9407246e299c · outbound

This paper cites To enhance the temporal representations, we further refine the extracted temporal feature maps using a transformer module.

Contrastive Order Learning: A General Framework for Ordinal Regression To enhance the temporal representations, we further refine the extracted temporal feature maps using a transformer module

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:57:07.721710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1c30370e-8fe3-4d42-8bba-220cd0aab324 · outbound

This paper cites Table 9 shows that ConOrd achieves the best performance, outperforming all prior methods on both datasets.

Contrastive Order Learning: A General Framework for Ordinal Regression Table 9 shows that ConOrd achieves the best performance, outperforming all prior methods on both datasets

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:57:07.716379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 11edfd0c-cbf4-49b5-ab2b-dbc9816ecb94 · outbound

This paper cites (a) Successful cases (b) Failure case 22℃ [34℃]1℃ [1℃] 11℃ [11℃] 17℃ [17℃] 21℃ [21℃] 30℃ [30℃] Figure 8.Examples of regression results on the SkyFinder dataset.

Contrastive Order Learning: A General Framework for Ordinal Regression (a) Successful cases (b) Failure case 22℃ [34℃]1℃ [1℃] 11℃ [11℃] 17℃ [17℃] 21℃ [21℃] 30℃ [30℃] Figure 8.Examples of regression results on the SkyFinder dataset

Reference 16

Resolution: malformed identifier; raw_fallback, observed 2026-07-10T12:57:07.701991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b00bc3e5-01e5-4183-8bc6-cacbea2f6cb2 · outbound

This paper cites The gradient norms differ moderately in scale but remain consistently bounded and settle quickly into steady ranges.

Contrastive Order Learning: A General Framework for Ordinal Regression The gradient norms differ moderately in scale but remain consistently bounded and settle quickly into steady ranges

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:57:07.723557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f6872aec-e886-46e0-971c-5da22db45601 · outbound

This paper cites an unresolved cited work.

Contrastive Order Learning: A General Framework for Ordinal Regression Unresolved cited work

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-10T12:57:07.547671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8157e3a4-67a7-4427-a8bd-7f3e7a5f1168 · outbound

This paper cites Table 31.Training time per epoch on BID and KonIQ-10k.

Contrastive Order Learning: A General Framework for Ordinal Regression Table 31.Training time per epoch on BID and KonIQ-10k

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T12:57:07.718112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.