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Paper Citation Record · LEDGER

Dynamic Sparse Training for Deep Reinforcement Learning

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2106.04217.

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

pith.paper-citation-record.v1
2106.04217 v3

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 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:16:29.055004Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:44:25.391582Z

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 aeb0dcd4-9a5e-4e31-ab05-4bde6923adfc · inbound

NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling cites this paper.

NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling Dynamic Sparse Training for Deep Reinforcement Learning

Reference 63

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:44:25.537900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T14:44:21.282780Z digest=sha256:ff44854fca17e221779797264b4212ebdf40b37d3892225b49f8e725c04f9879

Observation 84ea6e32-46c7-423a-aa9f-2140eee87339 · inbound

Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning cites this paper.

Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning Dynamic Sparse Training for Deep Reinforcement Learning

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-15T19:16:29.055004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:16:29.055004Z digest=sha256:7db43543606b3e0ddd405c3e2813bb52b29ef7222cc8d9c6b0bb230cc74025be