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Paper Citation Record · LEDGER

Deep Residual Reinforcement Learning

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1905.01072.

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

pith.paper-citation-record.v1
1905.01072 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 2026-08-19T06:32:44.657259+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:17:38.678696Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T08:04:28.817622Z

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 db81075a-fd52-40f1-a1e6-31e9be0ab235 · inbound

An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning cites this paper.

An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning Deep Residual Reinforcement Learning

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-16T12:17:38.678696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:17:38.678696Z digest=sha256:7a267347e4af10d817b95a78352aff0a99400f108f0112fe7a3760f4badecf7d

Observation 1523eb53-aa10-4a42-9a44-954e40951a6d · inbound

Touch begins where vision ends: Generalizable policies for contact-rich manipulation cites this paper.

Touch begins where vision ends: Generalizable policies for contact-rich manipulation Deep Residual Reinforcement Learning

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T00:31:46.189872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:31:46.189872Z digest=sha256:e9957b48633df2537ae80cfe277bf8f55533748458816ba8052d646b60f368a2

Observation 9bc18da1-eb9a-4d68-b4ce-da82232ce040 · inbound

AnyBody: Free-Form Whole-Body Humanoid Control from Arbitrary Keypoint Guidance cites this paper.

AnyBody: Free-Form Whole-Body Humanoid Control from Arbitrary Keypoint Guidance Deep Residual Reinforcement Learning

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:04:28.819014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-30T07:44:51.002937Z digest=sha256:b9da04f0966b3e19662c870784de8fa47c603638ec7dfc08f86458cba5ed8013