Paper Citation Record · LEDGER

Observational Overfitting in Reinforcement Learning

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1912.02975.

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

pith.paper-citation-record.v1
1912.02975 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:07:49.947665Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T09:04:53.161564Z

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 284a3bc7-1a9a-4435-ad07-f8998e363950 · inbound

Scaling Laws for Reward Model Overoptimization cites this paper.

Scaling Laws for Reward Model Overoptimization Observational Overfitting in Reinforcement Learning

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:04:53.169579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 53ec10e7-5769-4be0-b608-5c5b4be8cc77 · inbound

Evolution and The Knightian Blindspot of Machine Learning cites this paper.

Evolution and The Knightian Blindspot of Machine Learning Observational Overfitting in Reinforcement Learning

Reference 177

Resolution: unresolved; no resolver link, observed 2026-08-10T16:30:10.134144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09bcc3e7-ed47-4f63-a2b8-bc4aa3f068e4 · inbound

Efficient Reinforcement Learning Through Adaptively Pretrained Visual Encoder cites this paper.

Efficient Reinforcement Learning Through Adaptively Pretrained Visual Encoder Observational Overfitting in Reinforcement Learning

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-08T18:56:45.449121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e560523d-9194-440e-ad02-47776012ee6c · inbound

MIGT: Memory Instance Gated Transformer Framework for Financial Portfolio Management cites this paper.

MIGT: Memory Instance Gated Transformer Framework for Financial Portfolio Management Observational Overfitting in Reinforcement Learning

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-08T13:18:55.479689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44b2fa85-6c17-4a60-ae44-e894decbf37c · inbound

Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning cites this paper.

Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning Observational Overfitting in Reinforcement Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T22:07:49.947665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0db245f-0116-47fc-b940-4fb12dc81a83 · inbound

Online Training and Pruning of Deep Reinforcement Learning Networks cites this paper.

Online Training and Pruning of Deep Reinforcement Learning Networks Observational Overfitting in Reinforcement Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T17:05:16.229659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdf908dc-fec1-45d7-92ba-2c25e7c69e11 · 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 Observational Overfitting in Reinforcement Learning

Reference 235

Resolution: unresolved; no resolver link, observed 2026-08-12T00:48:46.564158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.