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Paper Citation Record · LEDGER

Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.13777.

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

pith.paper-citation-record.v1
2402.13777 v5

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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:20:36.669857Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T09:12:14.689207Z

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 7bbc88ad-efbd-4cf0-9dda-be2de6e039af · inbound

Decision Flow Policy Optimization cites this paper.

Decision Flow Policy Optimization Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:20:36.669857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:20:36.669857Z digest=sha256:828c6cf98c8ba5b9664f645120f348b83b6497e1cdef4bd5efbaa1b037443289

Observation cc276bc0-73ed-44cc-b2e5-05a00e1e9b09 · inbound

DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty cites this paper.

DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-19T09:12:14.692671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T09:09:51.531488Z digest=sha256:cace636a3fa4a414c5121352db41c15bd5871415271567b010246440053a441c