Paper Citation Record · LEDGER

Offline Reinforcement Learning with Fisher Divergence Critic Regularization

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2103.08050.

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

pith.paper-citation-record.v1
2103.08050 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 2026-08-12T06:34:41.77262+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:35:00.783466Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T15:35:10.940163Z

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 2efcb5ac-af78-41d8-8814-bfdcb59efcf1 · inbound

Is Conditional Generative Modeling all you need for Decision-Making? cites this paper.

Is Conditional Generative Modeling all you need for Decision-Making? Offline Reinforcement Learning with Fisher Divergence Critic Regularization

Reference 255

Resolution: verified exact; arxiv_id, observed 2026-05-15T15:35:10.943347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b69ac022-c0a2-430f-a3ba-355a92657723 · inbound

Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data cites this paper.

Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data Offline Reinforcement Learning with Fisher Divergence Critic Regularization

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T18:35:00.783466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b14da1d-ef77-4854-8252-b9dfe85f047f · inbound

SORREL: Suboptimal-Demonstration-Guided Reinforcement Learning for Learning to Branch cites this paper.

SORREL: Suboptimal-Demonstration-Guided Reinforcement Learning for Learning to Branch Offline Reinforcement Learning with Fisher Divergence Critic Regularization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T11:24:29.041728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12f3aa42-cfc7-4cde-bf2a-ed324aeeb224 · inbound

Value Flows cites this paper.

Value Flows Offline Reinforcement Learning with Fisher Divergence Critic Regularization

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-04T11:01:30.763300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.