Paper Citation Record · LEDGER

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning

As of 13 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2412.08880.

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

pith.paper-citation-record.v1
2412.08880 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:33:37.721942Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

36 of 36 outbound references displayed

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verified fuzzy12
unresolved22
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External citation measurements

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Outbound references

Observation 484da714-e99a-4520-b896-f63ea4633c16 · outbound

This paper cites Constrained policy optimization.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Constrained policy optimization

Reference 1

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Observation 614de274-5e77-4761-80bf-c28644564dc3 · outbound

This paper cites Maximum entropy inverse reinforcement learning in continuous state spaces with path integrals.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Maximum entropy inverse reinforcement learning in continuous state spaces with path integrals

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.307332Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a791a083-db0d-40e6-93c3-9d19b8d87889 · outbound

This paper cites Constrained markov decision processes with total cost criteria: Lagrangian approach and dual linear program.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Constrained markov decision processes with total cost criteria: Lagrangian approach and dual linear program

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.289432Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1db5df65-eda1-4c92-9873-86c4032d64d4 · outbound

This paper cites Constrained Markov decision processes.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Constrained Markov decision processes

Reference 4

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Observation 636cafb2-0f7b-4233-ad75-f1032fce1913 · outbound

This paper cites Convex optimization.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Convex optimization

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.552930Z

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Observation 93c8ef20-0422-4cfb-86d2-28ba9d322c2a · outbound

This paper cites Decision transformer: Reinforcement learning via sequence modeling.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Decision transformer: Reinforcement learning via sequence modeling

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.558683Z

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Observation 6b258255-db0c-43f1-a7bd-bd18cb70c4f6 · outbound

This paper cites Pybullet, a python module for physics simulation for games, robotics and machine learning, 2016.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Pybullet, a python module for physics simulation for games, robotics and machine learning, 2016

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.564869Z

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Observation 9256cbd1-13c6-4efa-8f2c-b3a2e828c268 · outbound

This paper cites Directional differentiability of optimal solutions under slater's condition.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Directional differentiability of optimal solutions under slater's condition

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.226032Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 71a64338-d0d0-4560-ad92-c457ed052236 · outbound

This paper cites Parenting: Safe Reinforcement Learning from Human Input.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Parenting: Safe Reinforcement Learning from Human Input

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:33:38.005117Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0deffe96-4c7c-4b64-bbfd-34b362135362 · outbound

This paper cites A comprehensive survey on safe reinforcement learning.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning A comprehensive survey on safe reinforcement learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.580345Z

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Observation 1d1f6f5a-aa67-4549-8be7-782a782f91a4 · outbound

This paper cites A primal-dual augmented lagrangian.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning A primal-dual augmented lagrangian

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.199580Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c38cf8b3-58f2-4f41-9428-ffadf8c3f167 · outbound

This paper cites Bullet-safety-gym: A framework for constrained reinforcement learning.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Bullet-safety-gym: A framework for constrained reinforcement learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.592440Z

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Observation 8643a124-d913-4c15-9b1b-750249d9db3b · outbound

This paper cites A Review of Safe Reinforcement Learning: Methods, Theory and Applications.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.597399Z

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Observation 5ee64d99-f8cb-4f9c-9fd2-da6482429ed3 · outbound

This paper cites Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.602358Z

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Observation 866f1926-a3d6-47a9-aa85-735a1e3990d0 · outbound

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

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Offline Reinforcement Learning with Implicit Q-Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.606897Z

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Observation a0e80708-02c8-4cf3-8516-cc6f0c593526 · outbound

This paper cites Conservative q-learning for offline reinforcement learning.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Conservative q-learning for offline reinforcement learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.612195Z

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Observation 6f5cde42-7188-4a64-b4b7-cf4fa14bf058 · outbound

This paper cites Optidice: Offline policy optimization via stationary distribution correction estimation.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Optidice: Offline policy optimization via stationary distribution correction estimation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.152117Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 14972fe8-b442-4a3d-9485-393ac1488e1b · outbound

This paper cites COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.622251Z

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Observation f31ca234-8c65-48e2-ae24-d88c464fbdfd · outbound

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

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.628179Z

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Observation 33bf6911-2cbc-4a33-befc-e5bf0747f0d2 · outbound

This paper cites Datasets and Benchmarks for Offline Safe Reinforcement Learning.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Datasets and Benchmarks for Offline Safe Reinforcement Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.634783Z

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Observation 1f0345e2-16b3-4acb-9857-da80b41b1e4f · outbound

This paper cites Constrained decision transformer for offline safe reinforcement learning.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Constrained decision transformer for offline safe reinforcement learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.137434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 16d8aabc-e554-40fc-a42a-dc56489c2632 · outbound

This paper cites Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.645535Z

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Observation cffaf56a-76eb-496b-89f8-c54cafa1ff6c · outbound

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

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.650823Z

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Observation a21cab1a-23d3-4346-9d9e-152408a0540a · outbound

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

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.656127Z

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Observation e4adc729-f884-4777-bc6c-968f6d854617 · outbound

This paper cites Trust Region Policy Optimization.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Trust Region Policy Optimization

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.661644Z

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Observation cccddb50-a740-4495-9b42-15adee25b7c5 · outbound

This paper cites Equivalence Between Policy Gradients and Soft Q-Learning.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Equivalence Between Policy Gradients and Soft Q-Learning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.667394Z

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Observation 3e162c79-8e30-482d-a879-d855d690bc2a · outbound

This paper cites Responsive safety in reinforcement learning by pid lagrangian methods.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Responsive safety in reinforcement learning by pid lagrangian methods

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.120946Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6216db71-c306-4fbf-8ee6-4d198cb6b999 · outbound

This paper cites Constraints penalized q-learning for safe offline reinforcement learning.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Constraints penalized q-learning for safe offline reinforcement learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.101582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d0a69486-bf64-44aa-aa04-b430122cc777 · outbound

This paper cites Primal-dual stochastic gradient method for convex programs with many functional constraints.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Primal-dual stochastic gradient method for convex programs with many functional constraints

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.085356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9eabaaed-dbf7-44b9-86f4-8d62f22dc0ca · outbound

This paper cites OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:33:37.808510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0e665c63-23ba-468e-a65e-3daf84174d1d · outbound

This paper cites Reachability constrained reinforcement learning.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Reachability constrained reinforcement learning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.067425Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8f5e93cf-c4d0-48de-afad-450c830f1720 · outbound

This paper cites Penalized Proximal Policy Optimization for Safe Reinforcement Learning.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Penalized Proximal Policy Optimization for Safe Reinforcement Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.700628Z

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Observation b5486b46-e347-47f7-9837-461c07eaa0ff · outbound

This paper cites Evaluating model-free reinforcement learning toward safety-critical tasks.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Evaluating model-free reinforcement learning toward safety-critical tasks

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.050910Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation da699856-f6a8-4d7e-b7eb-eca65762b5af · outbound

This paper cites First order constrained optimization in policy space.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning First order constrained optimization in policy space

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:33:38.034039Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b59b261b-3528-4132-90d9-c51b8f8f0880 · outbound

This paper cites Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.716533Z

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Observation 0dc13ffc-13f9-44e5-94dc-f1d0ab8f545c · outbound

This paper cites Maximum entropy inverse reinforcement learning.

FAWAC: Feasibility Informed Advantage Weighted Regression for Persistent Safety in Offline Reinforcement Learning Maximum entropy inverse reinforcement learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T17:33:37.721942Z

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