Paper Citation Record · LEDGER

Dynamical Priors as a Training Objective in Reinforcement Learning

As of 7 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2604.21464.

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

pith.paper-citation-record.v1
2604.21464 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-09T22:01:21.826493Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

21 of 21 outbound references displayed

verified exact3
verified fuzzy18
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b0841072-eb51-41bf-82b6-079d528f6e56 · outbound

This paper cites Human -level control through deep reinforcement learning.

Dynamical Priors as a Training Objective in Reinforcement Learning Human -level control through deep reinforcement learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.125110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 46b636fd-f7d9-4a18-9378-c45f3482a4ea · outbound

This paper cites Mastering the game of Go with deep neural networks and tree search.

Dynamical Priors as a Training Objective in Reinforcement Learning Mastering the game of Go with deep neural networks and tree search

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.146492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ca323e17-2b27-49e0-9cd5-0b4a22a20f01 · outbound

This paper cites Simple statistical gradient-following algorithms for connectionist reinforcement learning.

Dynamical Priors as a Training Objective in Reinforcement Learning Simple statistical gradient-following algorithms for connectionist reinforcement learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.131435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4c46d430-a8c8-4f4e-a5f5-2685776fec45 · outbound

This paper cites The neural basis of decision making.

Dynamical Priors as a Training Objective in Reinforcement Learning The neural basis of decision making

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.134860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3d40533a-2eee-4f33-9112-3d60497b6bc5 · outbound

This paper cites Probabilistic decision making by slow reverberation in cortical circuits.

Dynamical Priors as a Training Objective in Reinforcement Learning Probabilistic decision making by slow reverberation in cortical circuits

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.142723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 130c8a4e-d2e0-4dc7-b3b5-c468a1ce03a6 · outbound

This paper cites Neural correlates of evidence accumulation in a perceptual decision task.

Dynamical Priors as a Training Objective in Reinforcement Learning Neural correlates of evidence accumulation in a perceptual decision task

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.121672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fa895780-f8e7-48bc-83b9-792ba508da39 · outbound

This paper cites Evidence accumulation detected in BOLD signal using slow perceptual decision making.

Dynamical Priors as a Training Objective in Reinforcement Learning Evidence accumulation detected in BOLD signal using slow perceptual decision making

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.118194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 357d8633-dedd-47f0-91ea-f3623a57a441 · outbound

This paper cites Unifying and generalizing models of neural dynamics during decision-making.

Dynamical Priors as a Training Objective in Reinforcement Learning Unifying and generalizing models of neural dynamics during decision-making

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:21:05.522791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 911d944e-3d32-4dba-a819-180218596201 · outbound

This paper cites Real-time recurrent reinforcement learning.

Dynamical Priors as a Training Objective in Reinforcement Learning Real-time recurrent reinforcement learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.083563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 657e41f6-b68d-41a6-824f-bae00bd7de73 · outbound

This paper cites Continuous -time on -policy neural reinforcement learning of working memory tasks.

Dynamical Priors as a Training Objective in Reinforcement Learning Continuous -time on -policy neural reinforcement learning of working memory tasks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.101754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4b007fa9-f9c7-477d-9e98-c406e616fa68 · outbound

This paper cites Deep reinforcement learning with time-scale invariant memory.

Dynamical Priors as a Training Objective in Reinforcement Learning Deep reinforcement learning with time-scale invariant memory

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:21:05.555777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 28c2bfd4-0b19-4191-af5a-1fccc1acb1bf · outbound

This paper cites Multi -timescale memory dynamics extend task repertoire in a reinforcement learning network with attention -gated memory.

Dynamical Priors as a Training Objective in Reinforcement Learning Multi -timescale memory dynamics extend task repertoire in a reinforcement learning network with attention -gated memory

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.091214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 45021147-b9d9-4667-b059-861249a29d97 · outbound

This paper cites Non -stationary policy learning for multi-timescale multi -agent reinforcement learning.

Dynamical Priors as a Training Objective in Reinforcement Learning Non -stationary policy learning for multi-timescale multi -agent reinforcement learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.088169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b8054ab1-5b5a-4ef2-8415-edf7a329106c · outbound

This paper cites Simplified Temporal Consistency Reinforcement Learning.

Dynamical Priors as a Training Objective in Reinforcement Learning Simplified Temporal Consistency Reinforcement Learning

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:21:05.547354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0aab9c72-a295-4d2f-963e-4d1cdc3ef677 · outbound

This paper cites Exploiting multiple secondary reinforcers in policy gradient reinforcement learning.

Dynamical Priors as a Training Objective in Reinforcement Learning Exploiting multiple secondary reinforcers in policy gradient reinforcement learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.098206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6c9360b7-5c19-4312-833e-84d49f574447 · outbound

This paper cites The diffusion decision model: theory and data for two-choice decision tasks.

Dynamical Priors as a Training Objective in Reinforcement Learning The diffusion decision model: theory and data for two-choice decision tasks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.107344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 78e26003-2031-48b0-b1ee-198094ca00e9 · outbound

This paper cites The physics of optimal decision making: a formal analysis of models of performance in two -alternative forced-choice tasks.

Dynamical Priors as a Training Objective in Reinforcement Learning The physics of optimal decision making: a formal analysis of models of performance in two -alternative forced-choice tasks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.080027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bfbf78a2-a927-45a5-8070-8da1f8726779 · outbound

This paper cites Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey.

Dynamical Priors as a Training Objective in Reinforcement Learning Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.076178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 98e1a712-432d-4f6a-992f-ce84a74f9ee2 · outbound

This paper cites Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task.

Dynamical Priors as a Training Objective in Reinforcement Learning Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.094637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 52f965d8-da2b-47d5-bb2f-a41bc3eea513 · outbound

This paper cites Reward-based training of recurrent neural networks for cognitive and value-based tasks.

Dynamical Priors as a Training Objective in Reinforcement Learning Reward-based training of recurrent neural networks for cognitive and value-based tasks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.137803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 35bab022-206f-4287-a4c0-27bb397e690f · outbound

This paper cites Context-dependent computation by recurrent dynamics in prefrontal cortex.

Dynamical Priors as a Training Objective in Reinforcement Learning Context-dependent computation by recurrent dynamics in prefrontal cortex

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T15:15:41.128458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

No inbound Pith citation observations are available.