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Paper Citation Record · LEDGER

Reinforcement Learning in the Real World: A Survey of Statistical Challenges and Future Directions

As of 9 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 3 inbound Pith citation observations for arXiv:2601.15353.

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

pith.paper-citation-record.v1
2601.15353 v2

Coverage vector

measured 2 of 2 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T09:09:53.522461Z

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T07:35:56.679877Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T23:49:15.006610Z

Reference resolution

2 of 2 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 38586ef8-4bfb-4e30-a06e-20bc3e6cd2ff · outbound

This paper cites Offline Meta Learning of Exploration.

Reinforcement Learning in the Real World: A Survey of Statistical Challenges and Future Directions Offline Meta Learning of Exploration

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-03T09:09:53.416330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T09:09:53.416330Z digest=sha256:3b48f9b2f45089ce410fdf1181c6dcd0e60ca12d167f57bd4f01224cd056d30d

Observation 21904c4c-9910-44da-bd85-a2836baf8866 · outbound

This paper cites A Review of Off-Policy Evaluation in Reinforcement Learning.

Reinforcement Learning in the Real World: A Survey of Statistical Challenges and Future Directions A Review of Off-Policy Evaluation in Reinforcement Learning

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-03T09:09:53.522461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T09:09:53.522461Z digest=sha256:1f354aee96900d1888c417e1bfd3031bfecba780c622af647a838a5efc23d41a

Pith citing papers

Observation 2c17b700-8c59-459f-b0ac-73ab4422e4b7 · inbound

Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning cites this paper.

Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning Reinforcement Learning in the Real World: A Survey of Statistical Challenges and Future Directions

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-07-14T02:20:22.498368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T07:00:32.206081Z digest=sha256:f941c66d3e613603c21376e14e361249009e93a8f25653d481115304417a75d2

Observation 6d682d5f-2242-4a5e-9255-9b1b1406014f · inbound

Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning cites this paper.

Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning Reinforcement Learning in the Real World: A Survey of Statistical Challenges and Future Directions

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-07-14T02:20:22.498368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T23:47:53.282259Z digest=sha256:c0c2aed22aa43fe9a01a1573dd119ea5771dd85d99eb30e6d7e55befdc929306

Observation 348f570c-20ab-4a61-817b-31de6590a574 · inbound

A Diffusion-Model Subpopulation Digital Twin for Mobile Health Deployment: A Case Study on the HeartSteps Intervention cites this paper.

A Diffusion-Model Subpopulation Digital Twin for Mobile Health Deployment: A Case Study on the HeartSteps Intervention Reinforcement Learning in the Real World: A Survey of Statistical Challenges and Future Directions

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-01T07:35:56.679877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T07:35:56.679877Z digest=sha256:e29c62c5be58bdd3979077dfc7fec66a09e3ae890c07f20d2d2ce038e1e885cc