Paper Citation Record · LEDGER

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2505.23871.

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

pith.paper-citation-record.v1
2505.23871 v2

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:55:54.416203Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:01:15.443445Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T05:01:17.482077Z

Reference resolution

43 of 43 outbound references displayed

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verified fuzzy22
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f07df930-7dab-4be3-9ff6-a941c0221bf2 · outbound

This paper cites Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data

Reference 1

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Observation 6806c56b-80d0-4f93-bbda-f07b6239954e · outbound

This paper cites Offline Reinforcement Learning from Datasets with Structured Non-Stationarity.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Offline Reinforcement Learning from Datasets with Structured Non-Stationarity

Reference 2

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Observation ae3d6006-5349-4ead-8aad-7106da10dd1f · outbound

This paper cites Is conditional generative modeling all you need for decision making? In The Eleventh International Conference on Learning Representations, 2023.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Is conditional generative modeling all you need for decision making? In The Eleventh International Conference on Learning Representations, 2023

Reference 3

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Observation 4193ddd7-63bf-4de2-b501-5cff4344046b · outbound

This paper cites Uncertainty-based offline reinforcement learning with diversified q-ensemble.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Uncertainty-based offline reinforcement learning with diversified q-ensemble

Reference 4

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Observation 8fc1e53c-519f-4b0e-996e-c04cbfd6fe86 · outbound

This paper cites Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning

Reference 5

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Observation 0419cc4f-e479-4089-883d-e7c0c1657164 · outbound

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

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Decision transformer: Reinforcement learning via sequence modeling

Reference 6

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Observation 8b641ced-b476-4710-bf8c-e9cf78a61c58 · outbound

This paper cites Exact policy recovery in offline rl with both heavy-tailed rewards and data corruption.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Exact policy recovery in offline rl with both heavy-tailed rewards and data corruption

Reference 7

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Observation 901b35f6-a897-4991-b54a-fedcaa433656 · outbound

This paper cites Consistent diffusion meets tweedie: Training exact ambient diffusion models with noisy data.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Consistent diffusion meets tweedie: Training exact ambient diffusion models with noisy data

Reference 8

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Observation bf4502ff-5025-487b-8de7-5dd4ed9c70ca · outbound

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

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Reference 9

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Observation c858ef78-624f-42f4-acee-de67074b791c · outbound

This paper cites A minimalist approach to offline reinforcement learn- ing.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning A minimalist approach to offline reinforcement learn- ing

Reference 10

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Observation 70525bd3-df61-4f38-8570-38c8e52a4f78 · outbound

This paper cites Off-policy deep reinforcement learning with- out exploration.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Off-policy deep reinforcement learning with- out exploration

Reference 11

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Observation ce47875b-e531-4665-b6ec-30fae9c7a8db · outbound

This paper cites Why so pessimistic? estimating uncertainties for offline rl through ensembles, and why their independence matters.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Why so pessimistic? estimating uncertainties for offline rl through ensembles, and why their independence matters

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:57.837287Z

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Observation 7bb711e0-81f2-4b51-8742-16ae564a9b2c · outbound

This paper cites IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies

Reference 13

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Observation 044294f5-e2f2-4677-a284-ce6e4a52f95d · outbound

This paper cites Denoising diffusion probabilistic models.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Denoising diffusion probabilistic models

Reference 14

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Observation 71b1811b-c4c7-46d2-ad04-06838da71daf · outbound

This paper cites Planning with diffusion for flexible behavior synthesis.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Planning with diffusion for flexible behavior synthesis

Reference 15

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Observation 9dedea89-7914-4726-8c53-7e240630a2fd · outbound

This paper cites Offline reinforcement learning as one big sequence modeling problem.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Offline reinforcement learning as one big sequence modeling problem

Reference 16

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Observation e84a4cd2-cafa-47e9-bfc4-3cb71585a727 · outbound

This paper cites Neural stochastic differential equations for uncertainty-aware offline rl.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Neural stochastic differential equations for uncertainty-aware offline rl

Reference 17

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Observation c4d21d72-cb97-4cb4-8a73-bdef2ef490e0 · outbound

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

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Offline Reinforcement Learning with Implicit Q-Learning

Reference 18

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Observation 51bdfcb9-5299-48f8-92cf-56ca80169906 · outbound

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

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Conservative q-learning for offline reinforcement learning

Reference 19

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Observation 506ed5af-a7b9-447f-ab85-59acdc70cfa7 · outbound

This paper cites Offline reinforcement learning: Tutorial, review, and perspectives on open problems, 2020.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Offline reinforcement learning: Tutorial, review, and perspectives on open problems, 2020

Reference 20

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Observation 20eb3195-e3be-45c8-8419-0ff7be9c8d52 · outbound

This paper cites Survival instinct in offline reinforcement learning.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Survival instinct in offline reinforcement learning

Reference 21

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Observation e1eb5478-0d2b-4072-9b61-e5f6d10d193a · outbound

This paper cites ROPO: Robust Preference Optimization for Large Language Models.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning ROPO: Robust Preference Optimization for Large Language Models

Reference 22

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Observation 0d4f3c54-dde8-45f3-bd3a-d8f6fc392673 · outbound

This paper cites Adapt- diffuser: Diffusion models as adaptive self-evolving planners.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Adapt- diffuser: Diffusion models as adaptive self-evolving planners

Reference 23

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Observation 81d71945-2dc4-486e-8ea6-8491f145900c · outbound

This paper cites Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning

Reference 24

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Observation f2c5b186-0fa7-42c0-9625-32b4df67b044 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 25

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Observation edc02cc5-db76-450b-8169-b5808703197b · outbound

This paper cites Robust re- inforcement learning using offline data.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Robust re- inforcement learning using offline data

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:56.832793Z

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Observation a4fc0fb9-2b0a-4640-86f5-4b5c9827f731 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning High-resolution image synthesis with latent diffusion models

Reference 27

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Observation 1d7ba50d-9111-434f-bda0-5b5d009993a2 · outbound

This paper cites Distributionally robust model-based offline reinforcement learning with near-optimal sample complexity.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Distributionally robust model-based offline reinforcement learning with near-optimal sample complexity

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:56.620400Z

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Observation fa6ae2c6-7739-44b5-a371-55c774d36064 · outbound

This paper cites Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

Reference 29

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This paper cites Deep un- supervised learning using nonequilibrium thermodynamics.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Deep un- supervised learning using nonequilibrium thermodynamics

Reference 30

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Observation d95c7342-e74a-4a3f-9126-2545d5b18d35 · outbound

This paper cites Score-based generative modeling through stochastic differential equations.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Score-based generative modeling through stochastic differential equations

Reference 31

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Observation e72e98e9-8ea3-4648-9020-99c453556ca2 · outbound

This paper cites Diffusion policies as an expressive policy class for offline reinforcement learning.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Diffusion policies as an expressive policy class for offline reinforcement learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:56.382385Z

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Observation 397d09de-2df4-4cfc-b15f-04cefe7ba833 · outbound

This paper cites COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks

Reference 33

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Observation ae603eeb-7d7a-43b2-86bc-6f252b7d7d6a · outbound

This paper cites Tackling data corruption in offline reinforcement learning via sequence modeling.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Tackling data corruption in offline reinforcement learning via sequence modeling

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:56.317012Z

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Observation bec7e5bc-db01-4841-ab8d-ae899f31e0dc · outbound

This paper cites Rorl: Robust offline reinforcement learning via conservative smoothing.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Rorl: Robust offline reinforcement learning via conservative smoothing

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:56.126296Z

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Observation c2be624d-9675-487d-92de-65d134ad6429 · outbound

This paper cites Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs

Reference 36

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This paper cites Towards robust offline reinforcement learning under diverse data corruption.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Towards robust offline reinforcement learning under diverse data corruption

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:55.958959Z

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Observation c23335ab-2839-49a6-ba43-d10898ab60cb · outbound

This paper cites Dmbp: Diffusion model-based predictor for robust offline rein- forcement learning against state observation perturbations.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Dmbp: Diffusion model-based predictor for robust offline rein- forcement learning against state observation perturbations

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:55.796509Z

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Observation 942f13a5-48d8-4637-8b4e-3dcb9e0b5a7a · outbound

This paper cites Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption

Reference 39

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Observation 02a95ecd-77eb-4bc1-9265-743cc4e120cc · outbound

This paper cites Corruption-robust offline reinforcement learning with general function approximation.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Corruption-robust offline reinforcement learning with general function approximation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:55.607965Z

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Observation b9ecdb87-ee50-4795-8257-fb15e3942fd9 · outbound

This paper cites Robust Reinforcement Learning on State Observations with Learned Optimal Adversary.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Reference 41

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Observation 5871579f-6a8d-4d36-901e-99fe7a7e3c0c · outbound

This paper cites Robust deep reinforcement learning against adversarial perturbations on state observa- tions.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Robust deep reinforcement learning against adversarial perturbations on state observa- tions

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:55.473965Z

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Observation 3eac0b00-c5a7-4c4f-bb3a-438918897dbf · outbound

This paper cites medium-replay- v2.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning medium-replay- v2

Reference 43

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Source-reported events for the cited work

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Pith citing papers

Observation a4d3b03d-0631-4e30-a768-51c4b3a89431 · inbound

Ambient Diffusion Omni: Training Good Models with Bad Data cites this paper.

Ambient Diffusion Omni: Training Good Models with Bad Data ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:01:17.604728Z

Source-reported events for the cited work

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