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Paper Citation Record · LEDGER

Learning to run a Power Network Challenge: a Retrospective Analysis

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2103.03104.

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

pith.paper-citation-record.v1
2103.03104 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 2026-08-13T06:32:02.005865+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:16:21.538074Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T06:56:10.596863Z

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 949c29a3-b2b4-4b7a-98d6-7d27512d0e9c · inbound

InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma cites this paper.

InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma Learning to run a Power Network Challenge: a Retrospective Analysis

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-12T20:16:21.538074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:16:21.538074Z digest=sha256:034cdddfa7e3d397c56b00092ed7ad99bdd4b148c4692d7dff61425a8cd57977

Observation 879fc3a0-51cb-4990-b319-8f7a69ff20ea · inbound

Robust Defense Against Extreme Grid Events Using Dual-Policy Reinforcement Learning Agents cites this paper.

Robust Defense Against Extreme Grid Events Using Dual-Policy Reinforcement Learning Agents Learning to run a Power Network Challenge: a Retrospective Analysis

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T18:56:21.390206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:56:21.390206Z digest=sha256:dc675a969bb80004f3aa1ac1862db7500aba71864770458c7679abd8695aa5c2

Observation 1724816b-cf51-4bcd-af59-83a48ee0815e · inbound

Large-scale Grid Optimization: The Workhorse of Future Grid Computations cites this paper.

Large-scale Grid Optimization: The Workhorse of Future Grid Computations Learning to run a Power Network Challenge: a Retrospective Analysis

Reference 119

Resolution
unresolved
no resolver link, observed 2026-08-10T21:30:10.844757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:30:10.844757Z digest=sha256:2be85b787b285bdf74db5a9fc48d114e09074d7d0740dd912a09b6f3e072b546

Observation dc357dde-bada-4bf8-9bcc-07b9702c2def · inbound

Cyber-Physical Anomaly Detection in IoT-Enabled Smart Grids Using Machine Learning and Metaheuristic Feature Optimization cites this paper.

Cyber-Physical Anomaly Detection in IoT-Enabled Smart Grids Using Machine Learning and Metaheuristic Feature Optimization Learning to run a Power Network Challenge: a Retrospective Analysis

Reference 14

Resolution
malformed identifier
arxiv_id, observed 2026-05-22T06:56:10.598895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-22T06:55:54.820266Z digest=sha256:4f6b170f9bd90f9d4b70ddfb215eb22deeb45729902da14421dc946e5a34ec40

Observation 295407fc-4ef3-41cb-820f-602ce389aca2 · inbound

Audited Selective Verification for Risk-Controlled N-1 Thermal Contingency Screening under Deployment Shift cites this paper.

Audited Selective Verification for Risk-Controlled N-1 Thermal Contingency Screening under Deployment Shift Learning to run a Power Network Challenge: a Retrospective Analysis

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-02T05:57:55.806203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:57:55.806203Z digest=sha256:696c66acd4db065301eea041490934116b4da32b740e997cc61ed1f2e8c22489