Pith. sign in

Paper Citation Record · LEDGER

Guided Deep Reinforcement Learning for Articulated Swimming Robots

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2301.13072.

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

pith.paper-citation-record.v1
2301.13072 v1

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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:27:55.215394Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T10:41:58.260484Z

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 d2df6ed4-2e6c-427c-ab39-b79d7deaa2ab · inbound

Data-driven Approach for Interpolation of Sparse Data cites this paper.

Data-driven Approach for Interpolation of Sparse Data Guided Deep Reinforcement Learning for Articulated Swimming Robots

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-16T04:27:55.215394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:27:55.215394Z digest=sha256:e1686b345c214cf358bffec5f9660c3e84fc0ab16c7281cae0372198872ea47a

Observation 7c23183e-de7f-4a9a-acc2-a2cdd5622b58 · inbound

Enhancing Efficiency and Propulsion in Bio-mimetic Robotic Fish through End-to-End Deep Reinforcement Learning cites this paper.

Enhancing Efficiency and Propulsion in Bio-mimetic Robotic Fish through End-to-End Deep Reinforcement Learning Guided Deep Reinforcement Learning for Articulated Swimming Robots

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:41:58.264624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T10:41:56.738439Z digest=sha256:cac689fa6a61006e7e75e4bd8584c27c56378cc0d67f85b5d5e066df12d38bbb