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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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T10:07:53.748795Z digest=sha256:015a41b335be21fdb5b30b6787370b81909827b11609ca52e40938c6bd3cbe56

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-11T00:52:41.972226Z digest=sha256:92df0e1f3cd67664ab493d90b501f64e5f19f0ff34ccd23a5f46601c486fc430

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-14T20:32:00.361991Z digest=sha256:63772cc2bfcb1dfed6cef1602664a03e31beb364d60b64595a7676bb27f63972

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T13:18:02.382334Z digest=sha256:4cf3e553aa2ac5ed74d89d7d45ff7ffd28bb303168c065f568e5d086083058c3

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T08:33:05.952601Z digest=sha256:f6129bdf827e6b1d6749c3bb48e43d77b746af35f1382795246df99afc7e8fc0

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T15:14:03.455914Z digest=sha256:f46d3b96dab53a24770dc21710ea3bfd17b08e3a96f5f9ad2a9744658a9f9221

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-07-02T13:32:55.274187Z digest=sha256:1643ff98d9b5144fa94d636c132e7a3dd6b03ce868603dc65331505a85c77cce

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-07-02T04:31:33.375845Z digest=sha256:273785edb8ecc0c08845d6edc5f5207527b68388f9cad75e4622980948ca8635