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Paper Citation Record · LEDGER

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 9 inbound Pith citation observations for arXiv:2502.02316.

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

pith.paper-citation-record.v1
2502.02316 v2

Coverage vector

measured 79 of 79 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T12:38:14.369887Z

measured 88 of 88 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:28:41.716079Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:59:43.293825Z

Reference resolution

79 of 79 outbound references displayed

  • verified exact0
  • verified fuzzy32
  • unresolved45
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 203afd33-f713-4722-bd17-58eab248641f · outbound

This paper cites write newline.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning write newline

Reference 1

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no resolver link, observed 2026-08-09T12:38:14.087464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.087464Z digest=sha256:677c8e43233682f733082413544269a8a3a205cb5f94a01c72e546867cbc6fe4

Observation 0b88acfd-b643-49d0-81f6-9cd71d0fb879 · outbound

This paper cites an unresolved cited work.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Unresolved cited work

Reference 2

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raw_fallback, observed 2026-08-09T12:38:15.182823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.093314Z digest=sha256:a76436db1a1028b9109d57fcc29fe8395acceee05053be993f1fa00b32408fa6

Observation ee4f3bbf-ae68-44f5-bb53-dff5915592a1 · outbound

This paper cites S., Courville, A.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning S., Courville, A

Reference 3

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no resolver link, observed 2026-08-09T12:38:14.097793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.097793Z digest=sha256:2cb37e2248b7f991597da2ac44bf57256683ea6df13c136a29f82a3a3f0722eb

Observation 3a48d042-edd4-4ae0-9f7f-5076055408ed · outbound

This paper cites Iterated Denoising Energy Matching for Sampling from Boltzmann Densities.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Iterated Denoising Energy Matching for Sampling from Boltzmann Densities

Reference 4

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no resolver link, observed 2026-08-09T12:38:14.101529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.101529Z digest=sha256:eff2a07e214d4acb779591aa71701a629289ce8ce72a3dc89396a80576fcf3f5

Observation 1ec41a2f-6a9f-44b1-9967-682e6019bcb6 · outbound

This paper cites an unresolved cited work.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Unresolved cited work

Reference 5

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unresolved
no resolver link, observed 2026-08-09T12:38:14.105807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.105807Z digest=sha256:104078eefb1454cf976fd83dc825b32bc9b4cba3e3d42c97de258435e28c585e

Observation acf952e3-931d-467a-b8c5-3b34a8ce8f42 · outbound

This paper cites Efficient gradient-free variational inference using policy search.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Efficient gradient-free variational inference using policy search

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-09T12:38:15.154632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.109558Z digest=sha256:41c6722989e2ab45dbc63dc83bfa1323f95317332efdde5c33f6fd7527a27200

Observation 0a0eb642-e926-44f4-b258-70818517bb84 · outbound

This paper cites G., Dabney, W., and Munos, R.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning G., Dabney, W., and Munos, R

Reference 7

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no resolver link, observed 2026-08-09T12:38:14.113362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.113362Z digest=sha256:2bf16de3ecc79a4f4aad449fa3bbda8e0f933f00123bfe6e07f03fb2245c3c96

Observation 1e46971f-fe93-4dee-908a-e3e3943f2acc · outbound

This paper cites An optimal control perspective on diffusion-based generative modeling.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning An optimal control perspective on diffusion-based generative modeling

Reference 8

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raw_fallback, observed 2026-08-09T12:38:15.134988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.117266Z digest=sha256:c37299e3b936575b070bd4a4cd62cfbf0760a683306e854d3fdbbb2bd2fb6b0b

Observation c8944175-5d6f-43dd-9944-97d74e1ce9ff · outbound

This paper cites Crossq: Batch normalization in deep reinforcement learning for greater sample efficiency and simplicity.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Crossq: Batch normalization in deep reinforcement learning for greater sample efficiency and simplicity

Reference 9

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raw_fallback, observed 2026-08-09T12:38:15.123699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.120792Z digest=sha256:dd1f4b65374202904da1d0a1e6d8e4533148ccca51eb20f7dd3144bc07de3dcc

Observation 24adc66f-f8fd-4d60-9a19-b4e0607a3011 · outbound

This paper cites Underdamped diffusion bridges with applications to sampling.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Underdamped diffusion bridges with applications to sampling

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-09T12:38:15.111698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.124244Z digest=sha256:2cd52ebd54eb68d69507201218e5f8d2f002b9448e40080d70fb2b1296229029

Observation 33f623d8-5a90-49f1-b532-dcf9af660a1f · outbound

This paper cites End-to-end learning of gaussian mixture priors for diffusion sampler.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning End-to-end learning of gaussian mixture priors for diffusion sampler

Reference 11

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raw_fallback, observed 2026-08-09T12:38:15.100057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.128205Z digest=sha256:d160a0257391c8d4108d6f038cb64d9fd5fcbce74babc804e18482b99a621e3f

Observation 6df01a18-2c97-49ef-bbbd-a2ed5019a634 · outbound

This paper cites Openai gym, 2016.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Openai gym, 2016

Reference 12

Resolution
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raw_fallback, observed 2026-08-09T12:38:15.088157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.131657Z digest=sha256:0045eece5973ff36b3285e962b20d9d364fb84d9856a40211f00984ef27add72

Observation ce76b231-caf9-4a2b-8ba3-cd28ad1c8ff1 · outbound

This paper cites Tightness without Counterexamples: A New Approach and New Results for Prophet Inequalities.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Tightness without Counterexamples: A New Approach and New Results for Prophet Inequalities

Reference 13

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local_arxiv, observed 2026-08-09T12:38:14.567153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.135117Z digest=sha256:15efcccf2b7b9b3e2f6362e909ed3790b51e1673ec0ddf445aff6934b2133cca

Observation af2db694-a77b-4c8a-be46-091df0cbb3a6 · outbound

This paper cites Offline reinforcement learning via high-fidelity generative behavior modeling.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Offline reinforcement learning via high-fidelity generative behavior modeling

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-09T12:38:15.075686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.139164Z digest=sha256:cf5d0859ab8c459d5d8da79515c12af426e57bc084015df1c487621ce8b4c2d5

Observation 463b306f-e696-4d5d-a00e-8141d85cd41a · outbound

This paper cites Sequential Controlled Langevin Diffusions.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Sequential Controlled Langevin Diffusions

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.142543Z digest=sha256:9a4b58c9b089270a250288ac2a46042e6e18913ac2176031801622961b905cdb

Observation 656a7fcb-641d-49db-a591-b4ae7eeadf75 · outbound

This paper cites Sequential controlled langevin diffusions.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Sequential controlled langevin diffusions

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:15.064866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.145887Z digest=sha256:95ab42b7d1f42e32c8e04ee0cb7a1cc2023dcd2fed58b548783e899b21bd6377

Observation af58e749-21bc-44d5-9cb4-7d66cd8c2d97 · outbound

This paper cites Diffusion policy: Visuomotor policy learning via action diffusion.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Diffusion policy: Visuomotor policy learning via action diffusion

Reference 17

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no resolver link, observed 2026-08-09T12:38:14.148959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.148959Z digest=sha256:4992d4c42480ee3f168cd3a38471093ba38b6f1bda2a7ff84da5f935ca48166a

Observation 8be1a765-d9d0-4d70-8b05-ad06f40602ae · outbound

This paper cites an unresolved cited work.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Unresolved cited work

Reference 18

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no resolver link, observed 2026-08-09T12:38:14.151776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.151776Z digest=sha256:7d3c3194713bc735c631ea377f737c5f51f3885e23381cc46215b34a51d8301f

Observation a7279a3d-3df2-4438-bbbe-ad2886b1b3e9 · outbound

This paper cites A stochastic control approach to reciprocal diffusion processes.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning A stochastic control approach to reciprocal diffusion processes

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:15.038657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.154882Z digest=sha256:b6d68b3fe0d0409546814d1f7d6ea73d3192087e4b06c9d68a4d501a044cb54b

Observation e5e22f54-b8a5-40ec-8f10-5b7533763a68 · outbound

This paper cites Sequential monte carlo samplers.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Sequential monte carlo samplers

Reference 20

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no resolver link, observed 2026-08-09T12:38:14.157903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.157903Z digest=sha256:caa3c7f0ecde3a9b0fdce339f5251a64349bd8fa04b85c2f0f278cde3e71ef56

Observation 44b83fed-ed29-42bb-9776-08a3c386a602 · outbound

This paper cites Diffusion-based reinforcement learning via q-weighted variational policy optimization.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Diffusion-based reinforcement learning via q-weighted variational policy optimization

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:15.019019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.160824Z digest=sha256:071f5cdb7455873631324cb297b280c230286b64dae682d9f342a43fe255822b

Observation 38113b63-1b87-44a1-9ff4-3a91fb5f4048 · outbound

This paper cites and Jin, C.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning and Jin, C

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:15.000021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.163769Z digest=sha256:a4a32519beedd1f5fc5a874f5c8f1a88d35e7d50f12adb6ee81715959f7c3858

Observation 4e73b97f-d16e-44bc-8199-27bacc96820a · outbound

This paper cites G., and Strathmann, H.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning G., and Strathmann, H

Reference 23

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raw_fallback, observed 2026-08-09T12:38:14.988685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.167254Z digest=sha256:2bece0e38e24ba6e490ad2f805d7c05fbd8a98864e51aac9ebd351c978f96ff2

Observation 7c606447-b7d7-4c41-a6fb-043a47e367a8 · outbound

This paper cites Diffusion actor-critic: Formulating constrained policy iteration as diffusion noise regression for offline reinforcement learning.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Diffusion actor-critic: Formulating constrained policy iteration as diffusion noise regression for offline reinforcement learning

Reference 24

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raw_fallback, observed 2026-08-09T12:38:14.977582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.170851Z digest=sha256:ce939213b22b250b2ed1abde4474a6ec09b5bad27cfef6d242d0467e4a3d4faa

Observation 9513d163-9d7d-4f26-9adf-765f629775ab · outbound

This paper cites and Domke, J.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning and Domke, J

Reference 25

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no resolver link, observed 2026-08-09T12:38:14.174440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.174440Z digest=sha256:fda4fd4dec2b436992ff76ff462b1a94beded02c3a1580e4bebe98fc1f771f6f

Observation f0559be9-0003-4eec-ac08-c22b2a65e4e7 · outbound

This paper cites Reinforcement learning with deep energy-based policies.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Reinforcement learning with deep energy-based policies

Reference 26

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no resolver link, observed 2026-08-09T12:38:14.178080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.178080Z digest=sha256:45bcbeb0a103bb62f45ef218ed2a1805c958c63aeda836f3b99645acf841c9f3

Observation 27bf4433-5563-4170-8138-df713dab2298 · outbound

This paper cites Latent space policies for hierarchical reinforcement learning.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Latent space policies for hierarchical reinforcement learning

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.953089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.182904Z digest=sha256:efc41387bacbf741ce870369c38ba6d3315335f379bb4b13f695f62a109715d0

Observation 9d579252-3905-44b2-9baa-656604c177a0 · outbound

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

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.942335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.186408Z digest=sha256:85d24bc9562548cb317ab04492de6eee24bf8265763a064303f5d392bf25b6c4

Observation e8e530f3-f95b-423b-9935-697a180111ae · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Soft Actor-Critic Algorithms and Applications

Reference 29

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no resolver link, observed 2026-08-09T12:38:14.189969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.189969Z digest=sha256:088b2e0a7496f49315657f3d493a5f068670d204a733fb928439518ee3779b85

Observation 99b2ad79-7c1e-41aa-bb7f-361477653df9 · outbound

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

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies

Reference 30

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no resolver link, observed 2026-08-09T12:38:14.193834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.193834Z digest=sha256:671a9e3f3bd88da24003da8536c68ddeb36f9b17177a803933f434733eff90e9

Observation c395e1eb-532b-4fd5-b9a9-98c9649bfa0b · outbound

This paper cites an unresolved cited work.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Unresolved cited work

Reference 31

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unresolved
raw_fallback, observed 2026-08-09T12:38:14.930480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.197642Z digest=sha256:cd12773a60ff97e6b6ab79071a54069f035166147fa78fdf2f9bbf18795167b2

Observation b813972e-5a86-417c-8a3a-17c3f56d04a9 · outbound

This paper cites Denoising diffusion probabilistic models.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Denoising diffusion probabilistic models

Reference 32

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no resolver link, observed 2026-08-09T12:38:14.201237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.201237Z digest=sha256:3603cfbbe9a378e2443363785207a19461451b5f91ed84ed1893da67191e8421

Observation c4cd67f8-4626-4693-9bec-ce5961d57d34 · outbound

This paper cites Schr{\"o}dinger-F{\"o}llmer Sampler: Sampling without Ergodicity.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Schr{\"o}dinger-F{\"o}llmer Sampler: Sampling without Ergodicity

Reference 33

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no resolver link, observed 2026-08-09T12:38:14.204618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.204618Z digest=sha256:2626ce1949669b56d2f3ad99e13cd1b6976aa09bff953e17ffc21009d9647de5

Observation cc8de289-3168-40d6-87da-1bbb62609350 · outbound

This paper cites and Dayan, P.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning and Dayan, P

Reference 34

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unresolved
no resolver link, observed 2026-08-09T12:38:14.208548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.208548Z digest=sha256:9090bbebd3e7786c4ef34b49e01e0d7397613022b89a3672e0de93403a012ebe

Observation b30079e6-bd0e-4bdc-b0fd-08b46ee2c299 · outbound

This paper cites N., and Precup, D.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning N., and Precup, D

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.906381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.212244Z digest=sha256:45e708414e20da6ea546b0a78cc7111974b6cbc617dc12da038a38ea5aabd417

Observation e7811df2-12a0-49fb-85f8-da4e426314a7 · outbound

This paper cites Planning with diffusion for flexible behavior synthesis.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Planning with diffusion for flexible behavior synthesis

Reference 36

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no resolver link, observed 2026-08-09T12:38:14.215741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.215741Z digest=sha256:f6c227b4c5bc13aacc5241da61e2fa21df9930d4d278c3f04d57769f2cb4c981

Observation 0db103f9-73cf-4dbe-b5a4-f6b31590b611 · outbound

This paper cites Efficient diffusion policies for offline reinforcement learning.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Efficient diffusion policies for offline reinforcement learning

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.888260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.219173Z digest=sha256:c98114294d6e867bb89c6f75136cb6af8180818fed82629a1fc89211ccaefe8b

Observation 4a3676ed-ea1c-434d-bd8f-eb1b1a52240f · outbound

This paper cites Elucidating the design space of diffusion-based generative models.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Elucidating the design space of diffusion-based generative models

Reference 38

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source=arxiv_source observed=2026-08-09T12:38:14.222831Z digest=sha256:8cc8b505e58d835a17f2bfd65f38aaa804a691ba77e737aa1508660dba4ee02c

Observation 619b962a-90db-43ce-af48-88db610c544a · outbound

This paper cites Auto-Encoding Variational Bayes.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Auto-Encoding Variational Bayes

Reference 39

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source=arxiv_source observed=2026-08-09T12:38:14.226467Z digest=sha256:bc9692c462494acff5b8ed39cfb6b480f6deadc123bfa80dc212a865a18c9779

Observation 7d12ff7c-cc09-4caf-9e15-e7eae1c7b510 · outbound

This paper cites Batch reinforcement learning.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Batch reinforcement learning

Reference 40

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verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.870021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.230327Z digest=sha256:5a76c8c8e969a9007bfae93419adfb9ba76fcd4cfcf9a9838ce1421275a94bc6

Observation a4f75e3d-f77f-496d-b070-bb2927c87969 · outbound

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

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 41

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no resolver link, observed 2026-08-09T12:38:14.234145Z

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source=arxiv_source observed=2026-08-09T12:38:14.234145Z digest=sha256:008b4a9c7f7968581c74353bc6da1d0113e881c3b6665d9741c0729c2e55bd12

Observation f2638d14-02d0-4a9c-a77e-617b1d26d5a7 · outbound

This paper cites TOP - ERL : Transformer-based off-policy episodic reinforcement learning.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning TOP - ERL : Transformer-based off-policy episodic reinforcement learning

Reference 42

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raw_fallback, observed 2026-08-09T12:38:14.858848Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.238193Z digest=sha256:6ab0308de1ad563adf2396c4c63f961fd4956847232172a5c7e4c877f4d11cd2

Observation 4809b0cd-c429-4c4f-b974-d3063e183d79 · outbound

This paper cites Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient

Reference 43

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no resolver link, observed 2026-08-09T12:38:14.242058Z

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source=arxiv_source observed=2026-08-09T12:38:14.242058Z digest=sha256:63133dace9d4b442809e378f60c58c79ba6d67cc9d0be5181117689288be88e2

Observation 87c1541d-f4e7-4906-affb-894f06ebfd19 · outbound

This paper cites Contrastive energy prediction for exact energy-guided diffusion sampling in offline reinforcement learning.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Contrastive energy prediction for exact energy-guided diffusion sampling in offline reinforcement learning

Reference 44

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source=arxiv_source observed=2026-08-09T12:38:14.245151Z digest=sha256:4ee44ec555783bde28dc3d31d28798402b7a183e26d9c0a6751bf08455c043cb

Observation dadef05a-23ca-40c2-a96b-e75e2feae13f · outbound

This paper cites K., S nderby, S.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning K., S nderby, S

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.839088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.248289Z digest=sha256:7c277c9501d9690297755a754c29594dc3ebe8feac2f2cba81e2920c01a2e8d2

Observation 3e71aaa3-867c-479a-87cb-e80a15e5436f · outbound

This paper cites Diffusion-dice: In-sample diffusion guidance for offline reinforcement learning.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Diffusion-dice: In-sample diffusion guidance for offline reinforcement learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.827504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.251712Z digest=sha256:150bfc4baa5f59a362f66cb0f3711939ec99d4b9f78738991cee28eb48cc9817

Observation ee81219c-e089-40aa-86c3-9eda621f0f89 · outbound

This paper cites S 2 ac: Energy-based reinforcement learning with stein soft actor critic.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning S 2 ac: Energy-based reinforcement learning with stein soft actor critic

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.817002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.254946Z digest=sha256:652506ffcff920446aaae435602f9c0b016e748c8095be5c7596114a2cb2cf1d

Observation ec591d77-e5aa-410d-9103-9717ef832ab5 · outbound

This paper cites and Cygan, M.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning and Cygan, M

Reference 48

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-09T12:38:14.258104Z digest=sha256:3234e6f708e5895d30f66455448c68bdab032bd1407a2f08b9981c3f9d24032f

Observation 21ce8d20-963b-4570-b0b2-b1edcab3dbad · outbound

This paper cites Bigger, regularized, optimistic: scaling for compute and sample efficient continuous control.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Bigger, regularized, optimistic: scaling for compute and sample efficient continuous control

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.799394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.261037Z digest=sha256:649444dd294df766283b93718bdeb75ddc5b9b95c8ec6b0f1e7719e2d1cba75a

Observation 0d0cf4b9-2ca5-4469-9217-ad12a71951db · outbound

This paper cites Dynamical theories of Brownian motion, volume 101.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Dynamical theories of Brownian motion, volume 101

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.788288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.264042Z digest=sha256:47f4a4a45450e1a897d30646622c9210586e9e929d3e49eff7a976441866cd88

Observation 3e64df8a-1914-47a3-ae76-c34cd0f92849 · outbound

This paper cites A unified view of entropy-regularized Markov decision processes.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning A unified view of entropy-regularized Markov decision processes

Reference 51

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source=arxiv_source observed=2026-08-09T12:38:14.267814Z digest=sha256:cb8f9928835a3078742c06e3fc0f7ec372695d4707717bcdabe6c34faf4220f3

Observation faf27320-67d3-4d0b-9d64-e93315eb1116 · outbound

This paper cites The primacy bias in deep reinforcement learning.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning The primacy bias in deep reinforcement learning

Reference 52

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source=arxiv_source observed=2026-08-09T12:38:14.271660Z digest=sha256:3dadd7b74e2ebd7fbb83e568c25eaea721e9c8dd825e1406be189e118fe072f0

Observation 36c8d1e6-630b-49e8-904c-4fd4f53c5b79 · outbound

This paper cites Learned Reference-based Diffusion Sampling for multi-modal distributions.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Learned Reference-based Diffusion Sampling for multi-modal distributions

Reference 53

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source=arxiv_source observed=2026-08-09T12:38:14.275215Z digest=sha256:fa85100cda19309cf8a314a6a15fe3050737259ee06ad9a7712d8f101923e591

Observation 79dc8dc3-bef3-450e-8809-6ebb33be4dd1 · outbound

This paper cites Transport meets variational inference: Controlled monte carlo diffusions.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Transport meets variational inference: Controlled monte carlo diffusions

Reference 54

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-09T12:38:14.278880Z digest=sha256:35ead7b950e7af127106e15b28147315e1697367a53f5b8c5c56171609f03b7f

Observation 65b5d15c-9889-4cad-a67d-59fb089fc7c4 · outbound

This paper cites Learning a diffusion model policy from rewards via q-score matching.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Learning a diffusion model policy from rewards via q-score matching

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.761370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.282288Z digest=sha256:62663a6ac09872e2799a19bba28d73184b725fccc6339605bdf6ffe94c6616c4

Observation a09c9356-1294-41c0-aced-32c735fcf081 · outbound

This paper cites Hierarchical variational models.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Hierarchical variational models

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.748420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.286001Z digest=sha256:7439de827e1bff5405662e26ec94c33186870553970040806d93b2fed0c36ee5

Observation 48824140-2a73-4abc-8ac3-5b49f513846a · outbound

This paper cites Goal conditioned imitation learning using score-based diffusion policies.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Goal conditioned imitation learning using score-based diffusion policies

Reference 57

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verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.736983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.289502Z digest=sha256:6377000d600fd1b498294b6c4e5e350876318540983d6bf1b5c7c2ef5870695c

Observation bf533dbe-5035-4d60-95d8-7fc5f0b1272a · outbound

This paper cites and Berner, J.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning and Berner, J

Reference 58

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raw_fallback, observed 2026-08-09T12:38:14.725710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.293053Z digest=sha256:ca0e8854ea072c2c7035595e3d8d36cfa3fe874833af1b49f50ff561cbd579a2

Observation 8066ba5f-6ffb-4f13-aae4-5d5bfa5373fd · outbound

This paper cites and Solin, A.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning and Solin, A

Reference 59

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-09T12:38:14.296976Z digest=sha256:1188b35145255b1200659098a68c48fe4bb08dd4d1bf4bdd1d64c0afdc150ac2

Observation 49810f60-65f7-42f6-be15-4089eae599a3 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Deep unsupervised learning using nonequilibrium thermodynamics

Reference 60

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source=arxiv_source observed=2026-08-09T12:38:14.301800Z digest=sha256:8bb7fa07c1fd6d3fbed27d567c45573afdb3ddebbfb05b7455a5dff1a293278d

Observation 4a897596-edc0-4c6f-a83a-80b65c8d7af8 · outbound

This paper cites P., Kumar, A., Ermon, S., and Poole, B.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning P., Kumar, A., Ermon, S., and Poole, B

Reference 61

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no resolver link, observed 2026-08-09T12:38:14.305552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.305552Z digest=sha256:954d7bde8a2277aaeecf01638d72f5b77f3534fa2b541116e641e50f439a0899

Observation 8a635f3c-89eb-4d7e-8911-58e4c8084279 · outbound

This paper cites an unresolved cited work.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Unresolved cited work

Reference 62

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no resolver link, observed 2026-08-09T12:38:14.309171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.309171Z digest=sha256:1ee3c37412920307ac7ca77e5d5b724e8ee859d24eca890518c5f4bc7fb08c5a

Observation 185596b5-8064-407d-b48a-2920076db62b · outbound

This paper cites Robot trajectory optimization using approximate inference.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Robot trajectory optimization using approximate inference

Reference 63

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.312599Z digest=sha256:25e9061039af05ac5763a933b09131a2a3934cbdf81ac6206e25406045117ac9

Observation 9763709c-6b80-4d9c-8840-3b43a1535995 · outbound

This paper cites The Variational Gaussian Process.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning The Variational Gaussian Process

Reference 64

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no resolver link, observed 2026-08-09T12:38:14.316160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.316160Z digest=sha256:11d3fc35e6d8b8459f6207581577de8db66fcac681781856da0de4bef1e87d88

Observation ff43e272-9320-469a-8ee0-6c9e1396a6f4 · outbound

This paper cites dm\_control: Software and tasks for continuous control.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning dm\_control: Software and tasks for continuous control

Reference 65

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no resolver link, observed 2026-08-09T12:38:14.320118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.320118Z digest=sha256:6656ca23311f5a4bbcb78a56a35b6ef86aac3a4bf469c87bf34a5131f49f6b38

Observation 69b67f08-7650-40ed-a1b9-5f1687fedf9b · outbound

This paper cites and Raginsky, M.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning and Raginsky, M

Reference 66

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.323715Z digest=sha256:a5c810d97762aad8d86da438d5e1cb166707132f3b9e7b1100363047cd91492c

Observation e46bd896-c502-4a9e-abb2-6eaf23ffb790 · outbound

This paper cites S., and Doucet, A.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning S., and Doucet, A

Reference 67

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verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.665066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.327292Z digest=sha256:c2119c8a4f94ee5bfc94c23bca7e57206b945d4af6afb4dc7c24f55662364662

Observation 1c194d97-1288-425b-aac3-d239516cb03e · outbound

This paper cites u sken, N. Bayesian learning via neural schr \.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning u sken, N. Bayesian learning via neural schr \

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.653971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.331007Z digest=sha256:5ea7de0e9b27c34af44a1fd346b86d76ef6029d5b7289fbed9b60c9ba6410b3f

Observation 3f4c3ba9-d9a9-40e2-a540-ad9028288e9b · outbound

This paper cites A connection between score matching and denoising autoencoders.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning A connection between score matching and denoising autoencoders

Reference 69

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no resolver link, observed 2026-08-09T12:38:14.334714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.334714Z digest=sha256:d18f1a9e19a9579aa18b7ba43f706ff8add48693870b75473c43f9b2978a2ad8

Observation a017ff77-6f1f-454f-b3f9-96bd28d87566 · outbound

This paper cites Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning

Reference 70

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no resolver link, observed 2026-08-09T12:38:14.338402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.338402Z digest=sha256:00ccbca2e10eb1de7010458f9d97ed1d8911aa170cdbd80c379116abd275f07a

Observation d88d61d6-91e0-4f62-bfc3-e70fa9569d23 · outbound

This paper cites an unresolved cited work.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Unresolved cited work

Reference 71

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unresolved
raw_fallback, observed 2026-08-09T12:38:14.634493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.342096Z digest=sha256:6da361d230eed49a9f3e2a7f0ec35168bb8690e47403bc3c1c78bb24ece562cb

Observation 9a98b497-f72f-4c08-a67e-62799cf7fc74 · outbound

This paper cites J., and Zhou, M.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning J., and Zhou, M

Reference 72

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verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.623216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.345551Z digest=sha256:aff8db3c4ae24597fd0e1861042e06a989d3c4c50c8f81bcfd4fd80e76b7c5d0

Observation 27df332f-43c7-4b99-b0d4-4a8734bb82af · outbound

This paper cites and Teh, Y.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning and Teh, Y

Reference 73

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no resolver link, observed 2026-08-09T12:38:14.349023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.349023Z digest=sha256:f2d1b975483cb50209c9aa61ccca67a4942a3b96a91e8d3235b66ae50f1c90bf

Observation 7c3a774b-37f9-490d-853f-abe83da17fb7 · outbound

This paper cites Policy Representation via Diffusion Probability Model for Reinforcement Learning.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Policy Representation via Diffusion Probability Model for Reinforcement Learning

Reference 74

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no resolver link, observed 2026-08-09T12:38:14.352435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.352435Z digest=sha256:a80527c50a6b1347bd5d95adcb08a52f3d4bfdeea5c04c4bd180f074709019af

Observation c586b889-f9f7-41f2-bae9-420dbd3113fb · outbound

This paper cites Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization

Reference 75

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metadata mismatch
local_arxiv, observed 2026-08-09T12:38:14.419170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.356711Z digest=sha256:84992c5dfeea990e3a951b001a9046e0029d61449092abd3d67ef0900bd77f69

Observation d08cbb27-c32e-473a-908d-8bf8a07390c5 · outbound

This paper cites Path Integral Sampler: a stochastic control approach for sampling.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Path Integral Sampler: a stochastic control approach for sampling

Reference 76

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unresolved
no resolver link, observed 2026-08-09T12:38:14.360227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.360227Z digest=sha256:f3927291a1ee51e1a8a8cd479428747b9561c687d6d7f2f8687217fd11b790f6

Observation b879a459-e67a-4782-b1f2-ca061de9297b · outbound

This paper cites Variational distillation of diffusion policies into mixture of experts.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Variational distillation of diffusion policies into mixture of experts

Reference 77

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verified fuzzy
raw_fallback, observed 2026-08-09T12:38:14.604750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T12:38:14.363751Z digest=sha256:2693cbc78d4b38f46ae939db2ac4460a0944308d8672ac0bdfbd0d1e24d22933

Observation 1f801739-e362-4d39-832d-213bf9037dcb · outbound

This paper cites an unresolved cited work.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning Unresolved cited work

Reference 78

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unresolved
no resolver link, observed 2026-08-09T12:38:14.366824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.366824Z digest=sha256:44eeda56c608a5d1338847d1d51a0b880e064313f770e5cda36cd10fb803151d

Observation fb8be11c-3caf-4f86-8891-52385aa1d29e · outbound

This paper cites D., Maas, A.

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning D., Maas, A

Reference 79

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unresolved
no resolver link, observed 2026-08-09T12:38:14.369887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T12:38:14.369887Z digest=sha256:ad4d89c0af3a7c9882781dd1b1a9c0442e3a070d88f45d05dbecd8df47a23517

Pith citing papers

Observation 716b42f4-aae2-4756-8cff-99c54aa377b6 · inbound

Efficient Online Reinforcement Learning for Diffusion Policy cites this paper.

Efficient Online Reinforcement Learning for Diffusion Policy DIME:Diffusion-Based Maximum Entropy Reinforcement Learning

Reference 3

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unresolved
no resolver link, observed 2026-08-09T19:28:41.716079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T19:28:41.716079Z digest=sha256:81e6f5affaf66ff6b9d58ae45b46331da5ce308236fc89883aa423afbe6cd690

Observation 4f41f3bf-524c-4d7d-b5ec-4ce13f26c927 · inbound

Exploratory Diffusion Model for Unsupervised Reinforcement Learning cites this paper.

Exploratory Diffusion Model for Unsupervised Reinforcement Learning DIME:Diffusion-Based Maximum Entropy Reinforcement Learning

Reference 8

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unresolved
no resolver link, observed 2026-08-08T13:21:18.155791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:21:18.155791Z digest=sha256:6d13fef8f980b93c77da71a22992735aa933c66c23e9843f0b36250ce9fb10dc

Observation 196e2f66-e015-4103-afdd-e02e0063ebff · inbound

Towards Adaptive External Communication in Autonomous Vehicles: A Conceptual Design Framework cites this paper.

Towards Adaptive External Communication in Autonomous Vehicles: A Conceptual Design Framework DIME:Diffusion-Based Maximum Entropy Reinforcement Learning

Reference 25

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unresolved
no resolver link, observed 2026-08-05T19:28:32.623166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:28:32.623166Z digest=sha256:8c81599697bffb43c40e08cacae2de2ded5b509293337eff7d80518c4481e9fe

Observation 8d1c6be2-7ef3-4375-abe0-0e9490bfdf28 · inbound

Reinforcement Learning with Discrete Diffusion Policies for Combinatorial Action Spaces cites this paper.

Reinforcement Learning with Discrete Diffusion Policies for Combinatorial Action Spaces DIME:Diffusion-Based Maximum Entropy Reinforcement Learning

Reference 9

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verified exact
arxiv_id, observed 2026-05-21T21:15:38.660604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-21T21:14:54.053177Z digest=sha256:2879d96d695c4b81331fd88c871b4b40e5d3acca166b38f6c1f51a4f1b28c23f

Observation 05f10b2f-7194-469d-bc18-beb18aa47576 · inbound

Diffusion-Augmented Markov Decision Processes for Maximum Entropy Reinforcement Learning cites this paper.

Diffusion-Augmented Markov Decision Processes for Maximum Entropy Reinforcement Learning DIME:Diffusion-Based Maximum Entropy Reinforcement Learning

Reference 2019

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unresolved
no resolver link, observed 2026-08-03T19:12:08.549060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T19:12:08.549060Z digest=sha256:9a79bf69b40ff4173c059ecea71ceaaa21a6df4c563097b9f027da8983a124f3

Observation 381c37d3-3f20-4a73-ad9e-f78ea0c83536 · inbound

What Does Flow Matching Bring To TD Learning? cites this paper.

What Does Flow Matching Bring To TD Learning? DIME:Diffusion-Based Maximum Entropy Reinforcement Learning

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-15T16:36:17.860115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T16:32:29.432272Z digest=sha256:dd6f39b5fddc138c8968195bf6262670c5a6fda7f87c56c9152bbf2d33ec7bd6

Observation 7cac92bc-43fa-43a4-be54-8d13bcb37acb · inbound

GeMPO: Generalized Measure Matching for Online Diffusion Reinforcement Learning cites this paper.

GeMPO: Generalized Measure Matching for Online Diffusion Reinforcement Learning DIME:Diffusion-Based Maximum Entropy Reinforcement Learning

Reference 6

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unresolved
no resolver link, observed 2026-07-14T23:47:45.866615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T23:47:45.866615Z digest=sha256:2f6085fb68864f3cc5e4456f9ece7bc851c04385e08e821828db29a5a7b0381b

Observation ced346c7-6915-4d10-92b2-1a7f1e1466dc · inbound

GenPO++: Generative Policy Optimization with Jacobian-free Likelihood Ratios cites this paper.

GenPO++: Generative Policy Optimization with Jacobian-free Likelihood Ratios DIME:Diffusion-Based Maximum Entropy Reinforcement Learning

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-02T16:27:08.518956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T22:47:10.062975Z digest=sha256:3bcc0f09a0dcc05202c627c524dc80e79d36c2eba1b5005c6c442da0a9474161

Observation 7de4cdf8-7b7b-45db-a400-1f8dc992d368 · inbound

Scalable Maximum Entropy Reinforcement Learning for Diffusion Policies via Adjoint Matching cites this paper.

Scalable Maximum Entropy Reinforcement Learning for Diffusion Policies via Adjoint Matching DIME:Diffusion-Based Maximum Entropy Reinforcement Learning

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:59:43.295757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T10:38:05.185415Z digest=sha256:feaa0c2a453cfd417f9643e404cc4ee7e55a7f9bc5139dd607e64f7c5c255dc3