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Paper Citation Record · LEDGER

Mildly Conservative Q-Learning for Offline Reinforcement Learning

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2206.04745.

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

pith.paper-citation-record.v1
2206.04745 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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:12:40.505647Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T07:55:15.837433Z

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 b0c20bb4-f22b-4b12-ae36-fcdfd60e549b · inbound

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning cites this paper.

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning Mildly Conservative Q-Learning for Offline Reinforcement Learning

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:55:15.841431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-15T07:55:15.678348Z digest=sha256:da3b4d315d24c4b11514e02bdbbcf6f16f7a548abf2cfd00f039c8d251ed75a9

Observation 2d820841-9616-4482-8e8b-d0bdac66fc8f · inbound

Are Expressive Models Truly Necessary for Offline RL? cites this paper.

Are Expressive Models Truly Necessary for Offline RL? Mildly Conservative Q-Learning for Offline Reinforcement Learning

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-11T15:12:40.505647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:12:40.505647Z digest=sha256:e0324910ca4d0cd04e18595bcf31816020f271ad3308c129a14f9322efe76b6d