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Paper Citation Record · LEDGER

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making

As of 9 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2507.15356.

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

pith.paper-citation-record.v1
2507.15356 v3

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:37:53.152448Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

30 of 30 outbound references displayed

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  • verified fuzzy12
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation a76a9418-e491-4598-86f4-58217c38bf00 · outbound

This paper cites Is Conditional Generative Modeling all you need for Decision-Making?.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Is Conditional Generative Modeling all you need for Decision-Making?

Reference 1

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source=pdf_text observed=2026-08-06T15:37:50.184495Z digest=sha256:4693e0a827c143f791dc7a75eccea6b2166cacfac462f2426c03275e9549e963

Observation 30860b91-1577-4040-985c-0b72487a98a8 · outbound

This paper cites Decision transformer: Reinforcement learning via sequence modeling.Advances in neural information processing systems, 34:15084–15097, 2021.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Decision transformer: Reinforcement learning via sequence modeling.Advances in neural information processing systems, 34:15084–15097, 2021

Reference 2

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source=pdf_text observed=2026-08-06T15:37:50.255255Z digest=sha256:e90a6a6cb99751a555f2e7f2645715833954296ac56ee1578b733f15677173f9

Observation d5c97db9-1a8e-44de-80b8-ca512574d786 · outbound

This paper cites Bail: Best-action imitation learning for batch deep reinforcement learning.Advances in Neural Information Processing Systems, 33:18353–18363, 2020.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Bail: Best-action imitation learning for batch deep reinforcement learning.Advances in Neural Information Processing Systems, 33:18353–18363, 2020

Reference 3

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Observation 47113f23-51c2-46fe-9590-5fe20bba8a3c · outbound

This paper cites Semi-markov offline reinforcement learning for healthcare.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Semi-markov offline reinforcement learning for healthcare

Reference 4

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source=pdf_text observed=2026-08-06T15:37:50.439573Z digest=sha256:e1650a1aee104d110dee9db2f469105a7e7216e86b89ef13ad56f4f556084d23

Observation 07fbdc61-538f-4b36-b0b2-7dcb7e3e48d8 · outbound

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

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Reference 5

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source=pdf_text observed=2026-08-06T15:37:50.561083Z digest=sha256:d5ea7bc3f45ec77af222f18365810b7e1e6d2edb467b00c9ff51edda600d9dc8

Observation 54ae3b4d-ee18-4c8a-b3c5-9c492e7bbd06 · outbound

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

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:37:50.638152Z digest=sha256:a00cc0bf96544c7949ef396e63c6d52464aa9ebb2b6046babc16ec0263ccaa49

Observation 1cc395fd-3a72-403a-8c89-f4f84ef09c21 · outbound

This paper cites Rediffuser: Reliable decision-making using a diffuser with confidence estimation.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Rediffuser: Reliable decision-making using a diffuser with confidence estimation

Reference 7

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:37:50.746400Z digest=sha256:47952899133cd1898aa44b55ff43b491d61842faea982f6f31e8ebf0170d162d

Observation fb909b41-48b6-4d68-957f-6c019ca2aae3 · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:37:50.864634Z digest=sha256:e263e36e0ef8bf9238272693dbc6536ea47ef3cb57f1c33e5d2d51fafb4e2a54

Observation 59d1e5b5-c75a-41dc-a1d9-9ee6e0b80539 · outbound

This paper cites Planning with Diffusion for Flexible Behavior Synthesis.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Planning with Diffusion for Flexible Behavior Synthesis

Reference 9

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source=pdf_text observed=2026-08-06T15:37:50.951988Z digest=sha256:e3f38d574beecc1f886ad453a15d995747dfe064962bf77dd59fa0d2b9bd5727

Observation 7f78e584-f1cb-4e89-a48b-2ac6943d9ab1 · outbound

This paper cites Offline reinforcement learning as one big sequence modeling problem.Advances in neural information processing systems, 34:1273–1286, 2021.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Offline reinforcement learning as one big sequence modeling problem.Advances in neural information processing systems, 34:1273–1286, 2021

Reference 10

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source=pdf_text observed=2026-08-06T15:37:51.017352Z digest=sha256:d7f8017ff80934c5dddc2608e20ee71dc4077e119e587e67a7aa5aee43fee295

Observation 85c565e6-3faf-4e2d-bf89-871b02cc75e7 · outbound

This paper cites MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale

Reference 11

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source=pdf_text observed=2026-08-06T15:37:51.099837Z digest=sha256:8c79f9bc0398c43ffc6ecab409502b8cf6c95043272bdd99309d40ab10e73ca9

Observation 40859e80-6de1-459e-a428-baf474a65320 · outbound

This paper cites Morel: Model-based offline reinforcement learning.Advances in neural information processing systems, 33:21810–21823, 2020.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Morel: Model-based offline reinforcement learning.Advances in neural information processing systems, 33:21810–21823, 2020

Reference 12

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source=pdf_text observed=2026-08-06T15:37:51.194387Z digest=sha256:41b73ac5e17462ec775ed4f59a4a0d44d5b876d3dd9f48a793b2956e6e8a5356

Observation 43a1d839-1ac2-437c-b95a-ae85c13f853e · outbound

This paper cites Adam: A Method for Stochastic Optimization.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Adam: A Method for Stochastic Optimization

Reference 13

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source=pdf_text observed=2026-08-06T15:37:51.282377Z digest=sha256:f05df003509e5bf91c337cd9b1f07197c1cd0ea898c5b1e62c9750856f8eb56a

Observation a1ba8dd4-94a7-4f26-b8c3-81f3c6cf6c5d · outbound

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

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Offline Reinforcement Learning with Implicit Q-Learning

Reference 14

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source=pdf_text observed=2026-08-06T15:37:51.370600Z digest=sha256:e8af4adf21830caa68030531a194d66c8d740f3f0b3100a493b404efeba291a0

Observation da7ba5ce-e97b-4969-8970-4aba80388222 · outbound

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

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 15

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source=pdf_text observed=2026-08-06T15:37:51.477144Z digest=sha256:e3a0ed0286b7d4cfb88129659b987583bf7abb44d49e4bf9597e3c398ec270e4

Observation b257feac-cb78-4411-86fc-7217bf60151a · outbound

This paper cites Ceil: Generalized contextual imitation learning.Advances in Neural Information Processing Systems, 36:75491–75516, 2023.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Ceil: Generalized contextual imitation learning.Advances in Neural Information Processing Systems, 36:75491–75516, 2023

Reference 16

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:37:51.596493Z digest=sha256:699dfdd2ff66c88d94e129df2f8211e055aa2c3e7c7ea2a0c34e527a83ca037d

Observation 48859532-af26-4812-8077-3c8dc2db1d14 · outbound

This paper cites Synthetic experience replay.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Synthetic experience replay

Reference 17

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source=pdf_text observed=2026-08-06T15:37:51.718497Z digest=sha256:17012a5e51f36986bb008ac36e883647ffbbda1f2e789b5ad9a240f07ebf5cf9

Observation cce50624-81b0-4c45-bf06-4ee7df5b2a0c · outbound

This paper cites Double check your state before trusting it: Confidence- aware bidirectional offline model-based imagination.Advances in Neural Information Processing Systems, 35:38218–38231, 2022.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Double check your state before trusting it: Confidence- aware bidirectional offline model-based imagination.Advances in Neural Information Processing Systems, 35:38218–38231, 2022

Reference 18

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source=pdf_text observed=2026-08-06T15:37:51.816235Z digest=sha256:0b17967c8971009184c811b6eafda69b556a0c7c2e9842b042bf3957ad2c75fb

Observation 911ad9aa-3fdb-4b84-92ad-a1fca77d468c · outbound

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

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

Reference 19

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source=pdf_text observed=2026-08-06T15:37:51.955819Z digest=sha256:9941cdced06d827d8831198d96a0656175896925b3156b2688529576b10c1048

Observation fb06dcd3-7321-4184-945a-729cc75c9bca · outbound

This paper cites A survey on offline reinforcement learning: Taxonomy, review, and open problems.IEEE Transactions on Neural Networks and Learning Systems, 2023.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making A survey on offline reinforcement learning: Taxonomy, review, and open problems.IEEE Transactions on Neural Networks and Learning Systems, 2023

Reference 20

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source=pdf_text observed=2026-08-06T15:37:52.031493Z digest=sha256:d5d0da3bf7ca527178afc47558fa7d633534cdfb4c8e40a884e3d561cf8558c3

Observation 06fe5f51-8a19-4daa-80b3-f52fa83f3fff · outbound

This paper cites Offline Reinforcement Learning for Autonomous Driving with Safety and Exploration Enhancement.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Offline Reinforcement Learning for Autonomous Driving with Safety and Exploration Enhancement

Reference 21

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source=pdf_text observed=2026-08-06T15:37:52.125198Z digest=sha256:93d98d8751162caf0513bf0c8c329836a5e010b2fc01997663f276634ccec990

Observation d14a4f0e-edc8-4391-a6eb-f0d1e84a2d5a · outbound

This paper cites Deep unsuper- vised learning using nonequilibrium thermodynamics.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Deep unsuper- vised learning using nonequilibrium thermodynamics

Reference 22

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source=pdf_text observed=2026-08-06T15:37:52.224012Z digest=sha256:d2405901f38c0ec4b49e7d172f6a876536621ecdb5a9fea82147d26edcaf5188

Observation d0a87f13-2e4f-42f8-b744-8985202f3e58 · outbound

This paper cites Efficient exploration in continuous-time model-based reinforcement learning.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Efficient exploration in continuous-time model-based reinforcement learning

Reference 23

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source=pdf_text observed=2026-08-06T15:37:52.316078Z digest=sha256:5d81cb150ea0a08949a64fa1bedb5dbb56c04b4c6920a72ba50117a5f21c60c0

Observation 03bdb8d9-ee11-4ff5-9c05-efa8396597c7 · outbound

This paper cites Offline reinforcement learning with reverse model-based imagination.Advances in Neural Information Processing Systems, 34:29420–29432, 2021.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Offline reinforcement learning with reverse model-based imagination.Advances in Neural Information Processing Systems, 34:29420–29432, 2021

Reference 24

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source=pdf_text observed=2026-08-06T15:37:52.441854Z digest=sha256:1c83dd570beec28b76df9a35bb91fe3ad87e9f075c894aa01c89794c0cd0aed7

Observation fef7d80d-7fe6-4637-91e5-4d6c7920b2ff · outbound

This paper cites Boot- strapped transformer for offline reinforcement learning.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Boot- strapped transformer for offline reinforcement learning

Reference 25

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source=pdf_text observed=2026-08-06T15:37:52.619162Z digest=sha256:125eb81aa4664335968b943fd477aa0e569c2e4b97410050777cb1fafa01759f

Observation d97484b4-55e2-4324-a4a2-df35d918ce21 · outbound

This paper cites Critic regularized regression.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Critic regularized regression

Reference 26

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source=pdf_text observed=2026-08-06T15:37:52.727678Z digest=sha256:23d763ad90552dab9f69462583da0bce700e6f7511287711947d09bb7670b92e

Observation 373773cd-e2a3-4955-a4e8-aa13b83c08dc · outbound

This paper cites Combo: Conservative offline model-based policy optimization.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Combo: Conservative offline model-based policy optimization

Reference 27

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source=pdf_text observed=2026-08-06T15:37:52.899938Z digest=sha256:7d74db4d08ab40c363658085fc07eb89cec0f0115e12efbb7975dd17bf2fa46c

Observation ad2f96c3-67bc-47dd-9753-81357462fe27 · outbound

This paper cites Mopo: Model-based offline policy optimization.Advances in Neural Information Processing Systems, 33:14129–14142, 2020.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Mopo: Model-based offline policy optimization.Advances in Neural Information Processing Systems, 33:14129–14142, 2020

Reference 28

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source=pdf_text observed=2026-08-06T15:37:53.000991Z digest=sha256:6ef8311588301bee85926aeb0dab600568f7bca4a3087667f48ad08ef33525c9

Observation 147a32ca-1c0b-4248-983f-2c81921b4c16 · outbound

This paper cites Uncertainty-driven trajectory truncation for data augmentation in offline reinforcement learning.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Uncertainty-driven trajectory truncation for data augmentation in offline reinforcement learning

Reference 29

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source=pdf_text observed=2026-08-06T15:37:53.104913Z digest=sha256:0afbb47ee7e64f00c629bd62214229ebf39ca6bd82cc103fad3358cf34d6a0e0

Observation 42708a2e-4d3b-4adb-b0ae-58386157e9d3 · outbound

This paper cites Decision stacks: Flexible reinforcement learning via modular generative models.

RAD: Retrieval High-quality Demonstrations to Enhance Decision-making Decision stacks: Flexible reinforcement learning via modular generative models

Reference 30

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Pith citing papers

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