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Paper Citation Record · LEDGER

LightAutoML: AutoML Solution for a Large Financial Services Ecosystem

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2109.01528.

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

pith.paper-citation-record.v1
2109.01528 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:51:54.180605Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:07:37.125092Z

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 a1a4a066-7c06-4eb8-9c61-a122fc86d846 · inbound

Interpretable by Design: MH-AutoML for Transparent and Efficient Android Malware Detection without Compromising Performance cites this paper.

Interpretable by Design: MH-AutoML for Transparent and Efficient Android Malware Detection without Compromising Performance LightAutoML: AutoML Solution for a Large Financial Services Ecosystem

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T21:51:54.180605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:51:54.180605Z digest=sha256:ceac8b89d71fc58adfb036921d3c74ba7b550a44085982769e375384ed77050b

Observation 3d520d60-58a8-4a9c-96f1-cf2e9b4e9853 · inbound

Imbalanced Regression Pipeline Recommendation cites this paper.

Imbalanced Regression Pipeline Recommendation LightAutoML: AutoML Solution for a Large Financial Services Ecosystem

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-06T17:05:04.369380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:05:04.369380Z digest=sha256:8ad3a33bc11cf57e9f74229bb46b040bb153b5430fee7737b18f188d93250e7e

Observation 14714d9b-6e0a-4d41-af00-73d388b78834 · inbound

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems cites this paper.

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems LightAutoML: AutoML Solution for a Large Financial Services Ecosystem

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:22:51.738847Z

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=2026-05-18T22:22:19.478156Z digest=sha256:bba6f9b69dd2f7a4a9a3bd88db7117245b12ffa044d0823647563002ab50e94f

Observation da2f3360-d57d-4ea2-b2bf-ee6767351e45 · inbound

ML2B: Benchmarking LLMs on Cross-Lingual ML Pipeline Generation cites this paper.

ML2B: Benchmarking LLMs on Cross-Lingual ML Pipeline Generation LightAutoML: AutoML Solution for a Large Financial Services Ecosystem

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-04T14:52:49.910664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T14:52:49.910664Z digest=sha256:c3974ecf6a2bf29c2e852702c6393013df58028c7b242afdd74daa55d1385146

Observation 1217d351-7cda-468b-9f67-3eb7bf0a9670 · inbound

Pre-AF 13: An Interpretable Atrial Fibrillation Risk Score Mined from Discharge Reports cites this paper.

Pre-AF 13: An Interpretable Atrial Fibrillation Risk Score Mined from Discharge Reports LightAutoML: AutoML Solution for a Large Financial Services Ecosystem

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T04:07:37.126429Z

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=2026-06-27T14:07:47.862207Z digest=sha256:e0e363a58276787f21df9fd02c330d1a09bf0acd017b1ee30a7fcc1c03a65ab6