Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T11:22:57.874474Z
Paper Citation Record · LEDGER
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model
As of 21 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 1 inbound Pith citation observation for arXiv:2507.22854.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T15:07:17.743225Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-15T15:07:18.042953Z
Reference resolution
16 of 16 outbound references displayed
- verified exact1
- verified fuzzy10
- unresolved5
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 75fe3cf3-5c90-4468-bd2e-87fc122f11db · outbound
This paper cites Markov decision processes with their applications , vol- ume 14.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Markov decision processes with their applications , vol- ume 14
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T11:22:57.842621Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4818222d-efd6-4c52-9fad-972f49f8c88e · outbound
This paper cites Approximations and Learning for Continuous State and Action MDPs under Average Cost Criteria.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Approximations and Learning for Continuous State and Action MDPs under Average Cost Criteria
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T11:22:57.846867Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation de05e2e0-113e-441b-9c5e-e193260455b9 · outbound
This paper cites Almost optimal model-free reinforce- ment learningvia reference-advantage decomposition.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Almost optimal model-free reinforce- ment learningvia reference-advantage decomposition
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T11:22:58.102079Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 67e72fbd-9ef6-47f6-9b05-2f1f3fffb0e4 · outbound
This paper cites A Quantum Algorithm for Finding the Minimum.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model A Quantum Algorithm for Finding the Minimum
Reference 1998
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T11:22:57.829026Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18e15db9-9115-45ca-9938-caa8c5ed36a4 · outbound
This paper cites Improved Analysis of UCRL2 with Empirical Bernstein Inequality.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Improved Analysis of UCRL2 with Empirical Bernstein Inequality
Reference 2005
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T11:22:57.833805Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ab7710d8-836a-4d91-a4b9-2db33c708e67 · outbound
This paper cites Minimax regret bounds for reinforcement learning.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Minimax regret bounds for reinforcement learning
Reference 2006
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T11:22:58.190660Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation e68d45e1-769e-4625-98ba-b3e184298ee1 · outbound
This paper cites Logarithmic online regret bounds for undiscounted reinforcement learning.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Logarithmic online regret bounds for undiscounted reinforcement learning
Reference 2008
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T11:22:58.204202Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation fd105edd-8c00-41f0-9eea-5e0d78751993 · outbound
This paper cites Near-optimal regret bounds for reinforcement learning.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Near-optimal regret bounds for reinforcement learning
Reference 2012
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T11:22:58.217846Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 67ae80fc-2a13-42db-b016-b8c2233fdfb5 · outbound
This paper cites Improved regret bounds for undiscounted continuous reinforcement learning.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Improved regret bounds for undiscounted continuous reinforcement learning
Reference 2013
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T11:22:58.146322Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation fcb39ba7-a87b-49a5-835d-76a1daa5cb04 · outbound
This paper cites Quantum probability oracles & multidimensional amplitude estimation.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Quantum probability oracles & multidimensional amplitude estimation
Reference 2017
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T11:22:58.176021Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0556d1d9-6889-41e9-b3d4-aaf336d63979 · outbound
This paper cites Dynamic policy programming.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Dynamic policy programming
Reference 2018
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T11:22:58.231651Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ed7c7f1b-2f63-4f6f-8943-36aa2379ada7 · outbound
This paper cites Hernandez-Lerma.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Hernandez-Lerma
Reference 2020
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T11:22:58.160474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f54689f6-5d42-400b-a9bf-f0e1dfc99477 · outbound
This paper cites Near Sample-Optimal Reduction-based Policy Learning for Average Reward MDP.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Near Sample-Optimal Reduction-based Policy Learning for Average Reward MDP
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T11:22:57.865812Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b77448f8-06d7-44bd-b9a2-9dfae67d3fa4 · outbound
This paper cites Interactive value iteration for Markov decision processes with unknown rewards.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Interactive value iteration for Markov decision processes with unknown rewards
Reference 2022
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T11:22:58.117270Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f4f8c309-e9e0-4570-b2c3-ad3751b2b498 · outbound
This paper cites Learn- ing infinite-horizon average-reward MDPs with linear function approximation.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Learn- ing infinite-horizon average-reward MDPs with linear function approximation
Reference 2023
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T11:22:58.131921Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 87020556-fd2f-4104-b40c-d19aa609a1d4 · outbound
This paper cites Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities.
A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities
Reference 2024
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T11:22:57.934217Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Pith citing papers
Observation 73a7406c-769d-4718-a6bd-433367a55a14 · inbound
Improved Quantum Algorithms for Reinforcement Learning Under a Generative Model cites this paper.
Improved Quantum Algorithms for Reinforcement Learning Under a Generative Model A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T15:07:18.047918Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.