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Paper Citation Record · LEDGER

Submodularity In Machine Learning and Artificial Intelligence

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2202.00132.

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

pith.paper-citation-record.v1
2202.00132 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:47:43.011261Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T03:37:35.232087Z

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 6c73a10c-b19d-4f42-89b6-bbb1b2d90002 · inbound

MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models cites this paper.

MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Submodularity In Machine Learning and Artificial Intelligence

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-13T10:07:53.794000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-13T10:07:53.748795Z digest=sha256:5aa79b2bdc86f96474d9157b68aed015db027fd12953fe12680a138667f35b4b

Observation 28346ea3-1fb3-4d53-9bcb-da400756e2dc · inbound

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs cites this paper.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Submodularity In Machine Learning and Artificial Intelligence

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T12:47:43.011261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:47:43.011261Z digest=sha256:270b9951fb0feafad1e9344ca829ca859d882e5eeb742dba639b27bd8b4bc7b8

Observation ada8709e-93ba-4c3b-9024-b3c542f44dc4 · inbound

Robust Least Squares Problems with Binary Uncertain Data cites this paper.

Robust Least Squares Problems with Binary Uncertain Data Submodularity In Machine Learning and Artificial Intelligence

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-04T10:13:58.842695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:13:58.842695Z digest=sha256:ea6ca00bf68cf984b8b57a52905025ed4e9e4f52465df34da7cce3e75486761f

Observation d9836d13-7cf4-4e8c-b331-384ccbd0245f · inbound

Accelerated Relax-and-Round for Concave Coverage Problems cites this paper.

Accelerated Relax-and-Round for Concave Coverage Problems Submodularity In Machine Learning and Artificial Intelligence

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:05:57.075458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-11T00:52:41.972226Z digest=sha256:c3ba4715efd4b7a819fa1a00d590a710b7534e2c232c43c21bd2ca30d6dc54f9

Observation 41e25a10-01f4-49de-abec-f81ba440bba9 · inbound

SMA: Submodular Modality Aligner For Data Efficient Multimodal Learning cites this paper.

SMA: Submodular Modality Aligner For Data Efficient Multimodal Learning Submodularity In Machine Learning and Artificial Intelligence

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-14T20:32:56.596654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-14T20:32:00.361991Z digest=sha256:dd434172d9befb03674a3c3f1a443d95170b5d7f81102260c7fded337f204c89

Observation ba973b6c-f49c-4208-bd03-2ae66975c2b6 · inbound

Complement Submodular Information Measures for Balanced and Robust Data Selection cites this paper.

Complement Submodular Information Measures for Balanced and Robust Data Selection Submodularity In Machine Learning and Artificial Intelligence

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-06-30T13:24:40.230230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T13:18:02.382334Z digest=sha256:c3bd92af4f035a0e93ae18bdee2913be6c4c7d51454b84477144956003fa1792

Observation 94563602-b027-4df5-9cde-02316fde0025 · inbound

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions cites this paper.

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions Submodularity In Machine Learning and Artificial Intelligence

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-06-29T08:33:14.772666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-29T08:33:05.952601Z digest=sha256:d5a09cf41f58de282ec21a9e961225c79d8e271dd4ecc68022a8bc183b9c1f3a

Observation 21ea8ec0-5cb7-4200-8069-1fd20dfde975 · inbound

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions cites this paper.

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions Submodularity In Machine Learning and Artificial Intelligence

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-02T12:58:41.632832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T12:58:41.632832Z digest=sha256:72d0574b3b7fa407afce584e095a8672a61107aec0954ec85f4dae0aeeae8c2b

Observation 9e9a1fbb-1fe6-4a2d-86ac-43484eb71e5a · inbound

Submodular Optimization with Applications to Decision and Control cites this paper.

Submodular Optimization with Applications to Decision and Control Submodularity In Machine Learning and Artificial Intelligence

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-03T03:37:35.233423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-27T15:14:03.455914Z digest=sha256:a622daa74167e53a4defb5e2019f10cb4ac0c3c7c2f0ec516c2dc732cad49fe8

Observation 322e00e5-5ad4-47e9-a1c4-66b2d950b7ae · inbound

Recall Is Not Enough: A Reader-Context Diagnostic for Budget-Constrained Retrieval-Augmented Generation cites this paper.

Recall Is Not Enough: A Reader-Context Diagnostic for Budget-Constrained Retrieval-Augmented Generation Submodularity In Machine Learning and Artificial Intelligence

Reference 41

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T13:36:58.511304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-02T13:32:55.274187Z digest=sha256:0cef76e2465e2402471ea7b02116abd3cba396259c257908d4662fdcb82b9045

Observation ce978379-3edd-40a9-83e3-d6677f4944d2 · inbound

Submodular Maximization over Many Matroids via Ordered Local Search cites this paper.

Submodular Maximization over Many Matroids via Ordered Local Search Submodularity In Machine Learning and Artificial Intelligence

Reference 167

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T04:36:35.996952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-02T04:31:33.375845Z digest=sha256:f74253191c8b54fc1bbb4cd3f94dfec0a8315f0862fb0e5291bfa96217897d13