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Paper Citation Record · LEDGER

Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.21117.

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

pith.paper-citation-record.v1
2410.21117 v1

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:19:42.281297Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T05:19:42.375595Z

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 8a61dff1-b95c-4949-bd17-4e3b739159d7 · inbound

The interplay of robustness and generalization in quantum machine learning cites this paper.

The interplay of robustness and generalization in quantum machine learning Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization

Reference 56

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:19:42.381786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T05:19:42.281297Z digest=sha256:5909eb6fb5b38a01b72b110d9e34522149171c1f877da9cca603b0f6765c6c80

Observation b1561bf9-d03d-412a-97ca-733b4f93a709 · inbound

Diagnosing Simulation and Hardware Barriers to Cross-Size Transfer in Equivariant Quantum Reinforcement Learning cites this paper.

Diagnosing Simulation and Hardware Barriers to Cross-Size Transfer in Equivariant Quantum Reinforcement Learning Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-04T09:39:18.441025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:39:18.441025Z digest=sha256:9edc4b663795d61ac909a370b45e36dcf9e903bf8c2823696af85012e59d91b8