Paper Citation Record · LEDGER

Reinforcement Learning with Random Time Horizons

As of 20 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2506.00962.

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

pith.paper-citation-record.v1
2506.00962 v2

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:04:00.844121Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

verified exact2
verified fuzzy21
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c17865b5-f16c-417e-a61e-14af8991c27a · outbound

This paper cites M., and Sun, W.

Reinforcement Learning with Random Time Horizons M., and Sun, W

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:08.314379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3d79a602-1722-42b5-8dcc-109581632a6f · outbound

This paper cites An optimal control perspective on diffusion-based generative modeling.

Reinforcement Learning with Random Time Horizons An optimal control perspective on diffusion-based generative modeling

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:07.943354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 11848eba-7792-4a3a-8349-4313dd1673b4 · outbound

This paper cites Steady state analysis of episodic reinforcement learning.

Reinforcement Learning with Random Time Horizons Steady state analysis of episodic reinforcement learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:07.587976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7d63d11e-ac53-4719-9996-b3efa119e559 · outbound

This paper cites Finite-Sample Analysis of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning.

Reinforcement Learning with Random Time Horizons Finite-Sample Analysis of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:04:01.429448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6def04ef-1c65-4891-bbd3-dd906e61c7cd · outbound

This paper cites an unresolved cited work.

Reinforcement Learning with Random Time Horizons Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:04:07.258358Z

Source-reported events for the cited work

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Observation bb57821f-0633-4c4a-bde4-23972733b118 · outbound

This paper cites Finite state Markovian decision processes.

Reinforcement Learning with Random Time Horizons Finite state Markovian decision processes

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:06.807588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1d87063d-636e-4e13-9170-a787eb8f0b5f · outbound

This paper cites and Sch \"u tte, C.

Reinforcement Learning with Random Time Horizons and Sch \"u tte, C

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:06.403025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0438410c-f251-4002-a688-757897fd52a0 · outbound

This paper cites Variational characterization of free energy: Theory and algorithms.

Reinforcement Learning with Random Time Horizons Variational characterization of free energy: Theory and algorithms

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:06.142821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d7fc37ce-0105-45ca-a973-6348e1cdcb16 · outbound

This paper cites Fr\'{e}chet derivatives of expected functionals of solutions to stochastic differential equations.

Reinforcement Learning with Random Time Horizons Fr\'{e}chet derivatives of expected functionals of solutions to stochastic differential equations

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:04:01.138144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 40fdb2c6-5c4c-4d16-97fb-d3442c12ae7c · outbound

This paper cites Continuous control with deep reinforcement learning.

Reinforcement Learning with Random Time Horizons Continuous control with deep reinforcement learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:05.961251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e76d062e-9886-463a-884d-8ed878b4972b · outbound

This paper cites Online reinforcement learning with uncertain episode lengths.

Reinforcement Learning with Random Time Horizons Online reinforcement learning with uncertain episode lengths

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:05.662630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ff03ed89-d27d-491b-a17e-dde9b5b8bc02 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Reinforcement Learning with Random Time Horizons Playing Atari with Deep Reinforcement Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:03:58.652529Z

Source-reported events for the cited work

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Observation fb4803f5-2282-4267-bdea-77254ea5029f · outbound

This paper cites and Thomas, P.

Reinforcement Learning with Random Time Horizons and Thomas, P

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:05.402213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f83b191f-1f2c-4bbc-aedc-fded12b0ad2d · outbound

This paper cites and Richter, L.

Reinforcement Learning with Random Time Horizons and Richter, L

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:05.128034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 285f59f2-a65c-4643-9515-7d892ef44a37 · outbound

This paper cites Stochastic control foundations of autonomous behavior.

Reinforcement Learning with Random Time Horizons Stochastic control foundations of autonomous behavior

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:04.952143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fea4c62f-45d4-416b-aed7-d4b9cf0e2e99 · outbound

This paper cites Continuous-time stochastic control and optimization with financial applications, volume 61.

Reinforcement Learning with Random Time Horizons Continuous-time stochastic control and optimization with financial applications, volume 61

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:04.648176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 620359c4-2a76-4563-93ca-4493dc8d1dee · outbound

This paper cites an unresolved cited work.

Reinforcement Learning with Random Time Horizons Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T12:03:59.268173Z

Source-reported events for the cited work

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Observation ef440227-290e-422e-bb6f-112ee4e62c7e · outbound

This paper cites and Ribera Borrell, E.

Reinforcement Learning with Random Time Horizons and Ribera Borrell, E

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:04.333644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ea9911ac-36ec-477e-8832-9d4d67f16afd · outbound

This paper cites Improving control based importance sampling strategies for metastable diffusions via adapted metadynamics.

Reinforcement Learning with Random Time Horizons Improving control based importance sampling strategies for metastable diffusions via adapted metadynamics

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:03.911120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f08cd45a-5b85-4937-8c03-6786bf0f78e3 · outbound

This paper cites Trust region policy optimization.

Reinforcement Learning with Random Time Horizons Trust region policy optimization

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:03.590012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 48911a4b-217a-475a-967a-300416e5dee8 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Reinforcement Learning with Random Time Horizons Proximal Policy Optimization Algorithms

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T12:03:59.660830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26949471-6f45-4a5c-b5a4-1cd2faf1e4a7 · outbound

This paper cites Overcoming the timescale barrier in molecular dynamics: Transfer operators, variational principles and machine learning.

Reinforcement Learning with Random Time Horizons Overcoming the timescale barrier in molecular dynamics: Transfer operators, variational principles and machine learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:03.235858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0d10f094-e17d-4716-a164-1eab4003f514 · outbound

This paper cites Deterministic policy gradient algorithms.

Reinforcement Learning with Random Time Horizons Deterministic policy gradient algorithms

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:03.022097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 512c57e3-5cc5-4688-a4b3-e7b465b16bc0 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning with Random Time Horizons Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:04:02.819558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7646e382-a65e-4fb0-aff2-83722a1e2c91 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning with Random Time Horizons Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:04:02.645742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 11121e87-018f-471b-a95d-7e2d24782b50 · outbound

This paper cites S., McAllester, D., Singh, S., and Mansour, Y.

Reinforcement Learning with Random Time Horizons S., McAllester, D., Singh, S., and Mansour, Y

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T12:04:00.247441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08383ad2-08e0-4ec9-99b2-ab3491473147 · outbound

This paper cites U., De Cola, G., Deleu, T., Goulão, M., Kallinteris, A., Krimmel, M., KG, A., Perez-Vicente, R., Pierré, A., Schulhoff, S., Tai, J.

Reinforcement Learning with Random Time Horizons U., De Cola, G., Deleu, T., Goulão, M., Kallinteris, A., Krimmel, M., KG, A., Perez-Vicente, R., Pierré, A., Schulhoff, S., Tai, J

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:02.457682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 49aa1aca-32ea-4a76-8e4a-7c88dab3e0fc · outbound

This paper cites an unresolved cited work.

Reinforcement Learning with Random Time Horizons Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:04:02.298815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation eb154fd5-b6ac-41cd-bb99-d20188244c60 · outbound

This paper cites Unifying task specification in reinforcement learning.

Reinforcement Learning with Random Time Horizons Unifying task specification in reinforcement learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:02.124196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 066d052c-99c8-4bcb-a21f-1bb88685fb30 · outbound

This paper cites Global convergence of policy gradient methods to (almost) locally optimal policies.

Reinforcement Learning with Random Time Horizons Global convergence of policy gradient methods to (almost) locally optimal policies

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:01.909939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 53440e3e-290b-41e0-bdcc-7bd52c7f6e3f · outbound

This paper cites Actor-critic method for high dimensional static H amilton-- J acobi-- B ellman partial differential equations based on neural networks.

Reinforcement Learning with Random Time Horizons Actor-critic method for high dimensional static H amilton-- J acobi-- B ellman partial differential equations based on neural networks

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:04:01.708906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.