Paper Citation Record · LEDGER

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL

As of 18 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2608.03108.

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

pith.paper-citation-record.v1
2608.03108 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:57:30.265625Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

24 of 24 outbound references displayed

verified exact3
verified fuzzy1
unresolved18
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

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Outbound references

Observation 31556764-0c0c-4591-a04c-39bbbfdc47b2 · outbound

This paper cites OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.167094Z

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Unavailable: canonical work link unavailable.

Observation bcdfc21f-8072-4a17-8f5e-09af7b5279b6 · outbound

This paper cites Off-policy deep reinforcement learning without exploration.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Off-policy deep reinforcement learning without exploration

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.186527Z

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Observation 44011897-b9d1-4779-869c-538b49e3bca3 · outbound

This paper cites Improving Offline RL by Blending Heuristics.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Improving Offline RL by Blending Heuristics

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.195104Z

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Observation 69e91176-85a2-4f7b-8e62-19d3034dd66a · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Offline Reinforcement Learning with Implicit Q-Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.199368Z

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Observation b3de7287-9c74-4cb8-bc26-486b000c7a2a · outbound

This paper cites Conservative q-learning for offline reinforcementlearning.Advancesinneuralinformationprocessingsystems,33:1179–1191,2020.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Conservative q-learning for offline reinforcementlearning.Advancesinneuralinformationprocessingsystems,33:1179–1191,2020

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T14:57:30.757196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation de02cbe8-e3ec-48b8-86ef-df1050bf6ff4 · outbound

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

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.207852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ce00208-711a-4828-ad89-62c6a668c82e · outbound

This paper cites When Data Geometry Meets Deep Function: Generalizing Offline Reinforcement Learning.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL When Data Geometry Meets Deep Function: Generalizing Offline Reinforcement Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.212100Z

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Observation 3e6e6836-309c-49cd-9ff1-285174ff51cb · outbound

This paper cites Off-Policy Policy Gradient with State Distribution Correction.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Off-Policy Policy Gradient with State Distribution Correction

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.216181Z

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Observation 51416b22-4dde-452d-a45d-59278335e56e · outbound

This paper cites AWAC: Accelerating Online Reinforcement Learning with Offline Datasets.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.224473Z

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Observation 14b9d6b3-51b8-4049-aaad-e5cc55e07e01 · outbound

This paper cites Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.228498Z

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Observation 685f7411-20ce-4c0a-968f-f571d87c969c · outbound

This paper cites Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.244330Z

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Observation 6265a41e-95b0-4d24-8451-a58bb9a906f0 · outbound

This paper cites The In-Sample Softmax for Offline Reinforcement Learning.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL The In-Sample Softmax for Offline Reinforcement Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.248495Z

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Observation 092f5000-38bc-4cb8-a34a-c5af677ff58b · outbound

This paper cites Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-15T14:57:30.410209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bb8e6db4-684a-4092-97f0-f2ce8480b389 · outbound

This paper cites For Gym locomotion, each evaluation uses 10 trajectories, whereas each AntMaze evaluation uses 100 trajectories.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL For Gym locomotion, each evaluation uses 10 trajectories, whereas each AntMaze evaluation uses 100 trajectories

Reference 23

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T14:57:30.745195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cf67447e-6003-4453-b105-2009f791ce14 · outbound

This paper cites The mixture coefficient directly controls the amount of generalized information propagated by bootstrapping.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL The mixture coefficient directly controls the amount of generalized information propagated by bootstrapping

Reference 24

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T14:57:30.391627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8f33bbb0-e5d1-4be1-afd5-abcaa9635a06 · outbound

This paper cites Less is more: Clustered cross-covariance control for offline rl.arXiv preprint arXiv:2601.20765,.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Less is more: Clustered cross-covariance control for offline rl.arXiv preprint arXiv:2601.20765,

Reference 2001

Resolution: verified exact; raw_fallback, observed 2026-08-15T14:57:30.549823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 433cf653-0b74-44f2-9417-53b115e3f9be · outbound

This paper cites UNIQ: Conformal Calibration for Adaptive Conservatism in Offline Reinforcement Learning.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL UNIQ: Conformal Calibration for Adaptive Conservatism in Offline Reinforcement Learning

Reference 2016

Resolution: verified exact; local_arxiv, observed 2026-08-15T14:57:30.479977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1ec10dd5-0bad-4ef6-afaa-06772f177aeb · outbound

This paper cites Behavior Regularized Offline Reinforcement Learning.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Behavior Regularized Offline Reinforcement Learning

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.240241Z

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Observation 804d8ce9-a6bc-43be-a021-0c169128cbf5 · outbound

This paper cites Extreme Q-Learning: MaxEnt RL without Entropy.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Extreme Q-Learning: MaxEnt RL without Entropy

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.190639Z

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Observation de025adc-5ed7-48e6-a40c-1d068feefcc9 · outbound

This paper cites UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.176724Z

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Observation 952896ea-770e-4b55-855f-748acc8ccf9d · outbound

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

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.181451Z

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Observation fcd56ebf-da73-4c32-a269-bb0cb8890c48 · outbound

This paper cites Flow actor-critic for offline reinforcement learning.arXiv preprint arXiv:2602.18015,.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Flow actor-critic for offline reinforcement learning.arXiv preprint arXiv:2602.18015,

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.172608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f5d9b58-8389-43fe-a872-f437c8fd2cd9 · outbound

This paper cites Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.253091Z

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Unavailable: canonical work link unavailable.

Observation f18bcc3d-6db1-4cda-a9c5-31b83a18726a · outbound

This paper cites Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization.

Convex-Hull-Neighborhood Smooth Dual Generalization: Controlling Local Correction Propagation in Offline RL Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:30.220449Z

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Pith citing papers

No inbound Pith citation observations are available.