Paper Citation Record · LEDGER

Submodularity In Machine Learning and Artificial Intelligence

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 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 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:11:36.334568Z

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 2026-08-10T06:31:04.303077+00:00.

Observation 2e4e283d-aab2-442a-9bb0-16ab785df192 · inbound

Partitioning and Observability in Linear Systems via Submodular Optimization cites this paper.

Partitioning and Observability in Linear Systems via Submodular Optimization Submodularity In Machine Learning and Artificial Intelligence

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T15:11:36.334568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.