Paper Citation Record · LEDGER

Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2009.10795.

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

pith.paper-citation-record.v1
2009.10795 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:57:11.955008Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5531633e-afad-4aa1-bec4-d018de30fe39 · inbound

Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples cites this paper.

Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-08T11:57:11.955008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 528877d5-af5f-4d7e-ac4c-9695c5353db5 · inbound

Foundation Model Insights and a Multi-Model Approach for Superior Fine-Grained One-shot Subset Selection cites this paper.

Foundation Model Insights and a Multi-Model Approach for Superior Fine-Grained One-shot Subset Selection Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:27.259784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ec9656f-52f8-4eff-8313-8747d427221e · inbound

CDC: Causal Domain Clustering for Multi-Domain Recommendation cites this paper.

CDC: Causal Domain Clustering for Multi-Domain Recommendation Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T18:57:25.863188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b367549b-ac4b-4494-bcce-651483bb0d3b · inbound

Difficulty-Based Preference Data Selection by DPO Implicit Reward Gap cites this paper.

Difficulty-Based Preference Data Selection by DPO Implicit Reward Gap Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-21T23:50:47.716751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ee124e57-9986-4e32-aff1-854d506d411f · inbound

Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning cites this paper.

Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 153

Resolution: unresolved; no resolver link, observed 2026-08-05T22:09:10.325844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6eeea4f5-2ea9-4fde-987a-99c0a39a2251 · inbound

Ordinal Adaptive Correction: A Data-Centric Approach to Ordinal Image Classification with Noisy Labels cites this paper.

Ordinal Adaptive Correction: A Data-Centric Approach to Ordinal Image Classification with Noisy Labels Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-21T23:20:45.132324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 16c45af3-4ba2-4008-9823-2e23493f5bd2 · inbound

LiLAW: Lightweight Learnable Adaptive Weighting to Learn Sample Difficulty & Improve Noisy Training cites this paper.

LiLAW: Lightweight Learnable Adaptive Weighting to Learn Sample Difficulty & Improve Noisy Training Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T15:02:41.199727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 44d0bacf-b1b9-4253-aad8-fd41e1c78cfe · inbound

Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions cites this paper.

Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 287

Resolution: verified exact; arxiv_id, observed 2026-05-15T18:51:30.141583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 52ee057c-a174-4e71-9359-dfce68d8af03 · inbound

Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions cites this paper.

Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 287

Resolution: unresolved; no resolver link, observed 2026-08-02T20:04:34.119039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2475ba44-c8e6-41ba-a492-7264e5296f25 · inbound

Testing the Assumptions of Active Learning for Translation Tasks with Few Samples cites this paper.

Testing the Assumptions of Active Learning for Translation Tasks with Few Samples Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:55:58.629354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cbd2b06b-6228-49f6-a45c-2eafdd47fdf8 · inbound

COMPASS: COntinual Multilingual PEFT with Adaptive Semantic Sampling cites this paper.

COMPASS: COntinual Multilingual PEFT with Adaptive Semantic Sampling Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 114

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T13:41:05.705353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f7a34262-8719-469a-b5f8-53118da239f6 · inbound

Let the Target Select for Itself: Data Selection via Target-Aligned Paths cites this paper.

Let the Target Select for Itself: Data Selection via Target-Aligned Paths Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 39

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T02:51:17.953969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bec74757-bb6d-4b76-97b7-b68a8fb53a58 · inbound

Efficient, Validation-Free Intrinsic Quality Estimation for Large-Scale Face Recognition Datasets cites this paper.

Efficient, Validation-Free Intrinsic Quality Estimation for Large-Scale Face Recognition Datasets Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:53:16.463762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d444eb1b-8031-413b-91d2-ffb3b329f97d · inbound

The methodology of Constructing the Large-Scale Dataset for Detecting Presuicidal and Anti-Suicidal Signals in Social Media Texts in Russian cites this paper.

The methodology of Constructing the Large-Scale Dataset for Detecting Presuicidal and Anti-Suicidal Signals in Social Media Texts in Russian Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-05T00:54:50.761588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.