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Paper Citation Record · LEDGER

The Role of Coverage in Online Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2210.04157.

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

pith.paper-citation-record.v1
2210.04157 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:17:14.789543Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-07T14:33:54.431062Z

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 c93e8ac9-9a88-4775-88cc-de57cc13401d · inbound

Improving Environment Novelty Quantification for Effective Unsupervised Environment Design cites this paper.

Improving Environment Novelty Quantification for Effective Unsupervised Environment Design The Role of Coverage in Online Reinforcement Learning

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-08T18:17:14.789543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:17:14.789543Z digest=sha256:889b9b7903b9cdb96904e3f9bad7024ea925ad505cd732bcf86c854518a6c958

Observation c2a50976-2814-4905-8bed-c7b223b4a9a0 · inbound

Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits cites this paper.

Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits The Role of Coverage in Online Reinforcement Learning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T14:10:43.178507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:10:43.178507Z digest=sha256:de100ed336edf4791ea57b1544b88283fb9ca210c7d130d8c158785da2a8f0a7

Observation 2c102604-556e-4131-b27d-df8e3dfe5770 · inbound

Square$\chi$PO: Differentially Private and Robust $\chi^2$-Preference Optimization in Offline Direct Alignment cites this paper.

Square$\chi$PO: Differentially Private and Robust $\chi^2$-Preference Optimization in Offline Direct Alignment The Role of Coverage in Online Reinforcement Learning

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:03.851174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:03.851174Z digest=sha256:91fbc9eb15e476ad8280a040dda26910e16ced93fb6c5ae73df10224385ba976

Observation 3892cdd0-7f76-41af-b8f3-864fba48cbc5 · inbound

Towards Differentially Private Reinforcement Learning with General Function Approximation cites this paper.

Towards Differentially Private Reinforcement Learning with General Function Approximation The Role of Coverage in Online Reinforcement Learning

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:31:00.485398Z

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.

source=pdf_text observed=2026-05-11T01:15:59.533563Z digest=sha256:5bc037c79235ddd24846aad300478cd1d40503b61944d535630376999b6a69ac

Observation 0181aa0f-1da9-47ca-b620-91c5f072847a · inbound

Online KL-Regularized Reinforcement Learning with Function Approximation under Misspecification cites this paper.

Online KL-Regularized Reinforcement Learning with Function Approximation under Misspecification The Role of Coverage in Online Reinforcement Learning

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T12:06:55.869090Z

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.

source=pdf_text observed=2026-06-28T02:31:11.200818Z digest=sha256:a253c382c57620c8f734bb7c3e0789b347254c9a53e9880d04a7f7c7513ee113

Observation 652ebe5f-870a-42ed-ada9-2ab99a61889d · inbound

Online KL-Regularized Reinforcement Learning with Function Approximation under Misspecification cites this paper.

Online KL-Regularized Reinforcement Learning with Function Approximation under Misspecification The Role of Coverage in Online Reinforcement Learning

Reference 19

Resolution
unresolved
no resolver link, observed 2026-07-14T18:23:21.126826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T18:23:21.126826Z digest=sha256:a55b84a307143634af619589c60dba697d9122d5d15fad5242eb3e0a777118f4

Observation 23ae7914-0cfa-4e89-8e78-cca036e5460c · inbound

Quantile of Means: A Bonus-Free Ensemble Method for Minimax Optimal Reinforcement Learning cites this paper.

Quantile of Means: A Bonus-Free Ensemble Method for Minimax Optimal Reinforcement Learning The Role of Coverage in Online Reinforcement Learning

Reference 37

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T03:09:30.520219Z

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.

source=arxiv_source observed=2026-06-26T18:19:02.314185Z digest=sha256:6b748bbdc27e8c8beaef2fe843472ebe843836bd4ec36fbe2cc86fa405e3f89f

Observation 8fe57352-e744-4e40-8c98-4e47f29dc806 · inbound

Fitted Occupancy-Ratio Evaluation without Bellman Completeness cites this paper.

Fitted Occupancy-Ratio Evaluation without Bellman Completeness The Role of Coverage in Online Reinforcement Learning

Reference 90

Resolution
metadata mismatch
local_arxiv, observed 2026-07-07T14:33:54.432242Z

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.

source=arxiv_source observed=2026-07-07T14:25:33.921937Z digest=sha256:b63466c0b6c6b66c3fb5dd1f61179ea69e7fd58d73c271d4ab35c1a957d64ad1

Observation 3cc8a1c4-8378-4483-80d5-a2f527b6c14f · inbound

Fitted Occupancy-Ratio Evaluation without Bellman Completeness cites this paper.

Fitted Occupancy-Ratio Evaluation without Bellman Completeness The Role of Coverage in Online Reinforcement Learning

Reference 148

Resolution
unresolved
no resolver link, observed 2026-08-02T08:33:45.459641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T08:33:45.459641Z digest=sha256:5f86cf43f804a677d228e98d77407b47c4b8a71398edf20cc2639257361ab63b