Paper Citation Record · LEDGER

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure

As of 15 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2608.13549.

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

pith.paper-citation-record.v1
2608.13549 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:30:43.467104Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

17 of 17 outbound references displayed

verified exact1
verified fuzzy14
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 288e7952-c927-420b-b0b5-dda831095f77 · outbound

This paper cites Calibrated surrogate maximization of linear-fractional utility in binary classification.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Calibrated surrogate maximization of linear-fractional utility in binary classification

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:44.474744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 988b2dd6-4f0f-4d32-acec-1b560123f69b · outbound

This paper cites Blaschko.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Blaschko

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:44.385830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4e33082e-6eed-447a-bacb-052cf2f3caa0 · outbound

This paper cites A proof for the positive definiteness of the Jaccard index matrix.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure A proof for the positive definiteness of the Jaccard index matrix

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:44.355518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ea4c586d-8622-4c22-89b6-c825c604977d · outbound

This paper cites an unresolved cited work.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:30:44.280497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c1cbc7aa-da7b-49bf-9a6a-d2b1c8fb495a · outbound

This paper cites Finding the Jaccard median.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Finding the Jaccard median

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:44.237489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8ffc40ea-4204-454a-8f35-19a205dc97cb · outbound

This paper cites RankSEG : A consistent ranking-based framework for segmentation.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure RankSEG : A consistent ranking-based framework for segmentation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:44.180781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 396ce3b8-616c-4fab-81ba-dd3e8d6ca41d · outbound

This paper cites On label dependence and loss minimization in multi-label classification.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure On label dependence and loss minimization in multi-label classification

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:44.134752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a5168f9a-e8ee-40df-8c46-3223e17a1c88 · outbound

This paper cites Finocchiaro, Rafael Frongillo, and Enrique B.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Finocchiaro, Rafael Frongillo, and Enrique B

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:44.075567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c21ef081-4924-4b7b-af08-38e6b8bb2b39 · outbound

This paper cites an unresolved cited work.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:30:44.030528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 41135c66-1a97-4b88-93bb-ca5554d49371 · outbound

This paper cites Koyejo, Nagarajan Natarajan, Pradeep K.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Koyejo, Nagarajan Natarajan, Pradeep K

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:43.971533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c954a743-7164-4995-a090-c3929e0863dc · outbound

This paper cites Sharp analysis of learning with discrete losses.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Sharp analysis of learning with discrete losses

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:43.874753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0d34d6c4-4e33-44f3-9c1c-e35bb5b43abc · outbound

This paper cites Ramaswamy and Shivani Agarwal.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Ramaswamy and Shivani Agarwal

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:43.795709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation aab74cf5-fdcc-40b0-be23-c7cd44158e8b · outbound

This paper cites Ramaswamy and Shivani Agarwal.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Ramaswamy and Shivani Agarwal

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:43.705597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5b25f4f5-d1e7-44a2-9766-82d5ca12eb43 · outbound

This paper cites On the Bayes-optimality of F-measure maximizers.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure On the Bayes-optimality of F-measure maximizers

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:43.655350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fb5e3750-8d2f-4ec7-b872-6264f5cfc8c1 · outbound

This paper cites Learning submodular losses with the Lov\'asz hinge.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Learning submodular losses with the Lov\'asz hinge

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:43.601147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a48661d4-b03b-4ed7-95ea-0cdbaf61f39d · outbound

This paper cites Ramaswamy, and Shivani Agarwal.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Ramaswamy, and Shivani Agarwal

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:30:43.579504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ccb5c38d-2918-4908-8c36-2a4b5a4caeb2 · outbound

This paper cites Exact Rank and Convex Calibration Dimension Lower Bounds for the Multi-Label F1 Loss.

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure Exact Rank and Convex Calibration Dimension Lower Bounds for the Multi-Label F1 Loss

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-14T04:30:43.546100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.