Paper Citation Record · LEDGER

Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1910.03016.

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

pith.paper-citation-record.v1
1910.03016 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T01:10:35.315951Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T10:49:21.333777Z

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 96e16bea-87de-48e7-8f43-211d769ddfb2 · inbound

On the Power of Foundation Models cites this paper.

On the Power of Foundation Models Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-24T10:49:21.337440Z

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.

Observation 2f4554da-1ab3-4d1c-8dc2-a95567e596cf · inbound

Provably Efficient Offline-to-Online Value Adaptation with General Function Approximation cites this paper.

Provably Efficient Offline-to-Online Value Adaptation with General Function Approximation Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:55:24.138809Z

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.

Observation 090f3fcd-2d8b-471b-81c0-a6985f30d846 · inbound

Learning in Low-Dimensional Subspaces: Orthogonal Bottlenecks for Reinforcement Learning cites this paper.

Learning in Low-Dimensional Subspaces: Orthogonal Bottlenecks for Reinforcement Learning Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-12T15:59:38.060900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32918fac-bc60-4a91-aadb-b78dbce1245f · inbound

dtControl2+$\varepsilon$: Trading Optimality for Explainability in MDPs via Decision Trees cites this paper.

dtControl2+$\varepsilon$: Trading Optimality for Explainability in MDPs via Decision Trees Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T01:10:35.315951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.