Paper Citation Record · LEDGER

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks

As of 21 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2411.16421.

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

pith.paper-citation-record.v1
2411.16421 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:10:52.837080Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T13:14:51.329289Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T13:24:40.594032Z

Reference resolution

18 of 18 outbound references displayed

verified exact0
verified fuzzy10
unresolved7
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1c544b96-4c8c-4603-9814-d078c003a9aa · outbound

This paper cites A Simple Framework for Contrastive Learning of Visual Representations.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks A Simple Framework for Contrastive Learning of Visual Representations

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T13:10:52.760572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ce2e96f-0a2c-455b-a3d8-e4b26d09dbf9 · outbound

This paper cites Improved Baselines with Momentum Contrastive Learning.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Improved Baselines with Momentum Contrastive Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T13:10:52.765569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2118e0f-373e-40c8-8572-c50325edaa5c · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale, 2021.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks An image is worth 16x16 words: Transformers for image recognition at scale, 2021

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:10:53.088892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b3fc5459-84c3-497b-bc7d-b46fc8bf540b · outbound

This paper cites CenterNet: Keypoint triplets for object detection, 2019.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks CenterNet: Keypoint triplets for object detection, 2019

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:10:53.074739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 52283580-1f24-4c03-bf40-20737fd1a336 · outbound

This paper cites 100 Years of Progress in Tropical Cyclone Research.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks 100 Years of Progress in Tropical Cyclone Research

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:10:53.060424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7019e304-32f4-47f0-8798-505be929bb74 · outbound

This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation, 2014.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Rich feature hierarchies for accurate object detection and semantic segmentation, 2014

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:10:53.046351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 78b33e58-1807-42af-b0ad-127a69e3b5bf · outbound

This paper cites Deep residual learning for image recognition, 2015.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Deep residual learning for image recognition, 2015

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T13:10:52.788702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f79e435-57ce-4668-85b2-ac76def604e5 · outbound

This paper cites Long short-term memory.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Long short-term memory

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:10:53.024641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 898aa15b-b57c-41fd-8893-17d5b130402f · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T13:10:52.797246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7dee36e5-8ced-452f-9b0b-a81a7c5c67a6 · outbound

This paper cites Digital Typhoon Dataset V2.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Digital Typhoon Dataset V2

Reference 10

Resolution: malformed identifier; doi_truncated, observed 2026-08-12T13:10:52.870901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3465392d-d563-4850-a67b-d081e28c9d86 · outbound

This paper cites Digital typhoon: Long-term satellite image dataset for the spatio- temporal modeling of tropical cyclones.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Digital typhoon: Long-term satellite image dataset for the spatio- temporal modeling of tropical cyclones

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:10:53.001933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8a2626df-aaa1-4ad8-b334-4dab2dbf5e27 · outbound

This paper cites Knapp and Michael C.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Knapp and Michael C

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:10:52.988638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7dce064c-3161-4855-8323-9b2c014e9315 · outbound

This paper cites Knapp, Michael C.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Knapp, Michael C

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:10:52.975673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation da5cf6d4-18b2-42d2-8330-e8d7fc6f9b92 · outbound

This paper cites Operational Use of the Typhoon Intensity Forecasting Scheme Based on SHIPS (TIFS) and Commencement of Five-day Tropical Cyclone Intensity Forecasts.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Operational Use of the Typhoon Intensity Forecasting Scheme Based on SHIPS (TIFS) and Commencement of Five-day Tropical Cyclone Intensity Forecasts

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:10:52.962679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 405a5c17-2ea6-411e-bc95-6eae6c275bd5 · outbound

This paper cites You only look once: Unified, real-time object detection, 2016.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks You only look once: Unified, real-time object detection, 2016

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T13:10:52.823900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48bc90c6-5f2a-4846-83e2-4aa01229ec39 · outbound

This paper cites an unresolved cited work.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-12T13:10:52.939981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7a4c20f5-bce2-4c92-8642-9c2dfda2e4e5 · outbound

This paper cites U-Net: Convolutional networks for biomedical image segmentation, 2015.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks U-Net: Convolutional networks for biomedical image segmentation, 2015

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:10:52.926397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 82b6bf88-b5b9-4e39-9fd1-77dab25a333c · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks Representation Learning with Contrastive Predictive Coding

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T13:10:52.837080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 8543cac7-5fe7-481f-b64d-3a8a6a6df42e · inbound

The Perception-Physics Paradox: Probing Scientific Alignment with TC-Bench cites this paper.

The Perception-Physics Paradox: Probing Scientific Alignment with TC-Bench Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-30T13:24:40.595803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.