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Paper Citation Record · LEDGER

Robust Policy Gradient against Strong Data Corruption

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2102.05800.

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

pith.paper-citation-record.v1
2102.05800 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:58:13.612803Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:49:42.821102Z

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 89a41442-0c24-4b8a-9c40-0b924e3174c9 · inbound

Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning cites this paper.

Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning Robust Policy Gradient against Strong Data Corruption

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T13:58:13.612803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:58:13.612803Z digest=sha256:5ca93334c0e158ae428e6041c1639e6a019f558f69328b75ae9b5728e137221f

Observation 48b8132b-045e-4623-b204-d146b1db0f1e · inbound

Stationary Robust Mean-Field Games under Model Mismatches cites this paper.

Stationary Robust Mean-Field Games under Model Mismatches Robust Policy Gradient against Strong Data Corruption

Reference 103

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:49:42.822683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T10:50:40.841967Z digest=sha256:c587181bb8db8798a2ff862af7c4e83fb435b78723f0e803e4475c16b3267f2c