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Paper Citation Record · LEDGER

SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.15920.

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

pith.paper-citation-record.v1
2405.15920 v2

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:12:16.369455Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T22:15:49.906986Z

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 7d61603a-b393-4b2e-93af-449cbc1c193a · inbound

TRAM: Test-Time Risk Adaptation with Mixture of Agents cites this paper.

TRAM: Test-Time Risk Adaptation with Mixture of Agents SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-23T22:15:49.910336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-23T22:15:03.665956Z digest=sha256:19bba3d63844ecf90ff12dbda63f39c2c7026c092a9cb4032b363a5e548f80a8

Observation cbdc079c-5736-445d-9b5c-56fbde3de4e1 · inbound

Improving Performance of Spike-based Deep Q-Learning using Ternary Neurons cites this paper.

Improving Performance of Spike-based Deep Q-Learning using Ternary Neurons SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T11:12:16.369455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:12:16.369455Z digest=sha256:47fb8d8c57a9f9e48f58296afefcf2d9a50b4b372658d576a9c137ae5ed5527e