Pith. sign in

Paper Citation Record · LEDGER

Investigating Generalisation in Continuous 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:1902.07015.

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

pith.paper-citation-record.v1
1902.07015 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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T04:49:50.034743Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-25T04:50:20.950287Z

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 d23126c5-120d-4058-89d3-be396f421323 · inbound

VRLS: A Unified Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications cites this paper.

VRLS: A Unified Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications Investigating Generalisation in Continuous Deep Reinforcement Learning

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-05-24T18:04:47.386982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-24T18:00:26.313841Z digest=sha256:67e196296746671686b0def3114665fc501e7cc2ed82d877a79a620c53674a86

Observation f62e041e-feb9-4517-8c79-377f088ce770 · inbound

Understanding Goal Generalisation in Sequential Reinforcement Learning cites this paper.

Understanding Goal Generalisation in Sequential Reinforcement Learning Investigating Generalisation in Continuous Deep Reinforcement Learning

Reference 70

Resolution
verified exact
local_arxiv, observed 2026-05-25T04:50:20.953974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-25T04:49:50.034743Z digest=sha256:a7dc6e2061b82f19399fc4cc9f4f393393beab8f8640eece157dcfffe043776b