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Paper Citation Record · LEDGER

PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2305.15669.

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

pith.paper-citation-record.v1
2305.15669 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:19:29.370866Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T01:33:27.193926Z

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 a8f851a0-5087-40e1-879a-1118306b0361 · inbound

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation cites this paper.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-06T19:19:29.370866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:19:29.370866Z digest=sha256:cef1866dc5763fe04d3814ca2da4f88a2543d11b6a30744010323ea69918f6d6

Observation a521ed32-5016-4189-875c-5695f1d06c55 · inbound

Online Pre-Training for Offline-to-Online Reinforcement Learning cites this paper.

Online Pre-Training for Offline-to-Online Reinforcement Learning PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-06T18:27:02.388148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:27:02.388148Z digest=sha256:ceec9b590f779b4a159021c24d5ca997e7f176b0e594457c95679ed71b8711df

Observation 227a11f2-c231-4570-be1f-2d4df3c6b0d4 · inbound

The Three Regimes of Offline-to-Online Reinforcement Learning cites this paper.

The Three Regimes of Offline-to-Online Reinforcement Learning PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-04T13:00:07.558566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T13:00:07.558566Z digest=sha256:ff4af210c67152a6c35671898fa77025104daaf43472fa889d47efdc03f63cab

Observation 70215d69-c80b-4ef0-b858-61618f8bed27 · inbound

ROAD: Adaptive Data Mixing for Offline-to-Online Reinforcement Learning via Bi-Level Optimization cites this paper.

ROAD: Adaptive Data Mixing for Offline-to-Online Reinforcement Learning via Bi-Level Optimization PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-15T01:33:27.196250Z

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=2026-05-15T01:32:42.972836Z digest=sha256:42a9f624fff3918a4d97a9369677ddfce5f42bae789abc9743e84d7e9f0f23f3