Paper Citation Record · LEDGER

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief

As of 6 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2606.00680.

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

pith.paper-citation-record.v1
2606.00680 v3

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T12:46:51.707117Z

measured 11 of 11 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

11 of 11 outbound references displayed

verified exact0
verified fuzzy0
unresolved9
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a629de3d-813f-4809-87a8-2afad9e924dc · outbound

This paper cites Multi-Agent Deep Reinforcement Learning for Liquidation Strategy Analysis.

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief Multi-Agent Deep Reinforcement Learning for Liquidation Strategy Analysis

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T12:46:50.757117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 708f8489-5155-43e2-8091-ca5256625e5a · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T12:46:51.035841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c5fce21-f63a-4560-a4aa-de5af12edb14 · outbound

This paper cites Soft-Robust Algorithms for Batch Reinforcement Learning.

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief Soft-Robust Algorithms for Batch Reinforcement Learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T12:46:51.175897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0cc9998-7849-4936-8731-afdee212879c · outbound

This paper cites an unresolved cited work.

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief Unresolved cited work

Reference 10

Resolution: malformed identifier; no resolver link, observed 2026-08-02T12:46:51.429707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a3d9b67-0648-45cc-abcf-b3944efd32a4 · outbound

This paper cites HC” denotes the “HalfCheetah.

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief HC” denotes the “HalfCheetah

Reference 11

Resolution: malformed identifier; no resolver link, observed 2026-08-02T12:46:51.707117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d94b858-ee5a-41b2-8a96-06f786e65bac · outbound

This paper cites We provide a brief overview of the task below.

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief We provide a brief overview of the task below

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-02T12:46:51.373530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dda4bdf0-2a28-435e-b842-2f9e7fc58c6a · outbound

This paper cites D4RL: Datasets for Deep Data-Driven Reinforcement Learning.

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-02T12:46:50.820790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6626df48-ed06-4039-a9e1-05d6a92be0a1 · outbound

This paper cites Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials.

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-02T12:46:50.931186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9168516d-d94a-4c36-b044-4371cee555f1 · outbound

This paper cites PhyB achieves superior performance on 8 out of 12 benchmarks and delivers competitive results on the remaining.

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief PhyB achieves superior performance on 8 out of 12 benchmarks and delivers competitive results on the remaining

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-02T12:46:51.588128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38a1fbb3-aa9f-457a-b00e-8315243be804 · outbound

This paper cites Robust Regularized Policy Iteration under Transition Uncertainty.

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief Robust Regularized Policy Iteration under Transition Uncertainty

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-02T12:46:51.093159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34192b9c-ff45-4ec7-abeb-75c0da507b6f · outbound

This paper cites Long-Horizon Model-Based Offline Reinforcement Learning Without Explicit Conservatism.

Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief Long-Horizon Model-Based Offline Reinforcement Learning Without Explicit Conservatism

Reference 2026

Resolution: unresolved; no resolver link, observed 2026-08-02T12:46:51.287101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.