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Paper Citation Record · LEDGER

The Role of Deep Learning Regularizations on Actors in Offline RL

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.07606.

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

pith.paper-citation-record.v1
2409.07606 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:32:44.853450Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T03:37:13.779034Z

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 ede3ab45-31df-4fbd-8e7f-2d85145a3ba0 · inbound

SERNF: Sample-Efficient Real-World Dexterous Policy Fine-Tuning via Action-Chunked Critics and Normalizing Flows cites this paper.

SERNF: Sample-Efficient Real-World Dexterous Policy Fine-Tuning via Action-Chunked Critics and Normalizing Flows The Role of Deep Learning Regularizations on Actors in Offline RL

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-16T03:37:13.782582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-16T03:36:09.272019Z digest=sha256:4a54f7e7dc337211a18e6fb05e95a6c243b284617da018b73d36ce89049d0f33

Observation 3535bd9b-0478-4cba-b316-ca9feb83c891 · inbound

SERNF: Sample-Efficient Real-World Dexterous Policy Fine-Tuning via Action-Chunked Critics and Normalizing Flows cites this paper.

SERNF: Sample-Efficient Real-World Dexterous Policy Fine-Tuning via Action-Chunked Critics and Normalizing Flows The Role of Deep Learning Regularizations on Actors in Offline RL

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-03T02:55:50.805349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T02:55:50.805349Z digest=sha256:ae1c6ba0bb1f2e32a2afcfe070fa98bab5de3fe980d76f42635670f3c8cec953

Observation ddc44acd-bf88-4859-b41f-0fe1f7c57e96 · inbound

ReBRAC-v2: The Return of the King cites this paper.

ReBRAC-v2: The Return of the King The Role of Deep Learning Regularizations on Actors in Offline RL

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T00:32:44.853450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:32:44.853450Z digest=sha256:bcd6355afee5d2cf04e6e853a0b6b9a05edeb248d8c29f0bb6b4a2f96d28342d