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Paper Citation Record · LEDGER

Learning Temporally-Consistent Representations for Data-Efficient Reinforcement Learning

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2110.04935.

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

pith.paper-citation-record.v1
2110.04935 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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:48:43.752787Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T13:47:01.900860Z

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 88429711-d690-4385-b1fe-3d998623efc5 · inbound

Towards General-Purpose Model-Free Reinforcement Learning cites this paper.

Towards General-Purpose Model-Free Reinforcement Learning Learning Temporally-Consistent Representations for Data-Efficient Reinforcement Learning

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-10T13:47:01.904972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T13:47:01.651977Z digest=sha256:ff324ad0b7de99d950d716c09752608e91ab125e956bda9fe390dae742f4c46e

Observation 740f8dde-456b-467f-97e5-c227892f50db · inbound

V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control cites this paper.

V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control Learning Temporally-Consistent Representations for Data-Efficient Reinforcement Learning

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T00:48:43.752787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T00:48:43.752787Z digest=sha256:d170d417fdfd4f8354144f421884222a2e19571c3b115cd93cd9f93b5e68363b