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Paper Citation Record · LEDGER

DeepMind Control Suite

As of 23 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 100 inbound Pith citation observations for arXiv:1801.00690.

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

pith.paper-citation-record.v1
1801.00690 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-13T07:44:14.707183Z

measured 113 of 113 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 100 of 209 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:33:00.901351Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

13 of 13 outbound references displayed

  • verified exact9
  • verified fuzzy3
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

524
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 807f2362-7982-4495-b448-78c7a93bdd25 · outbound

This paper cites Layer Normalization.

DeepMind Control Suite Layer Normalization

Reference 1

Resolution
metadata mismatch
local_arxiv, observed 2026-05-13T07:44:14.738222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:a5282b74f962aa049fb08c986b6fdc97fd1651246750dea619bc57df5cce1ff8

Observation 3854d122-4ec6-4075-b192-77239ad98e89 · outbound

This paper cites doi: 10.1109/TSMC.1983.6313077.

DeepMind Control Suite doi: 10.1109/TSMC.1983.6313077

Reference 2

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verified exact
arxiv_id, observed 2026-05-13T07:44:14.725624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:9aa0302482cf79e880e760e5234fa5bbdbaa47bbca3fa7be47f0f6d32437ee36

Observation c67eab7a-90c3-417c-9ca5-afe34451d96e · outbound

This paper cites A Distributional Perspective on Reinforcement Learning.

DeepMind Control Suite A Distributional Perspective on Reinforcement Learning

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:44:14.732296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:af8b8d385246ad75a3ec8b0aa41510eca805344dde16b34000ad4ba0b72ccb78

Observation 5a9edccc-de44-4a74-82a2-bed0bbf8d511 · outbound

This paper cites Simulation tools for model-based robotics: Comparison of bullet, havok, mujoco, ode and physx.

DeepMind Control Suite Simulation tools for model-based robotics: Comparison of bullet, havok, mujoco, ode and physx

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T07:44:14.784086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:ffc1e66f5a7467c406e48f1e84331b8c007faf828945a143e3fa352edf85427d

Observation b009f6a1-d086-47c7-9cb7-80f05702153e · outbound

This paper cites Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control.

DeepMind Control Suite Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:44:14.763418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:c8b1f43f91a630684a2013aa88eb6d977a96df2369c7b557e7b8fbfdfa5622ba

Observation 1a4731eb-07d8-4429-831f-2985294a14b7 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

DeepMind Control Suite Adam: A Method for Stochastic Optimization

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-13T07:44:14.768962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:4ef7db48d928c7b8734c7c228838be3cc9de01904e398c974578296df1425381

Observation d1dcd187-9fbb-43ec-850f-2555dd775096 · outbound

This paper cites Continuous control with deep reinforcement learning.

DeepMind Control Suite Continuous control with deep reinforcement learning

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-05-13T07:44:14.774862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:70d4db974f0790e6d823b14b087f9fd30370fd41835816dd3e63601913ce236e

Observation 6cce8354-23d2-47f4-a76e-1a25442f3eda · outbound

This paper cites Learning human behaviors from motion capture by adversarial imitation.

DeepMind Control Suite Learning human behaviors from motion capture by adversarial imitation

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-06-04T18:11:00.280755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:fb70fc734e97fe5daa953f0d44006d8aa0c6442ab9788776c34f26f94ff0cbe5

Observation 696e50c7-cce6-4c80-9ffe-16489702aa79 · outbound

This paper cites Asynchronous Methods for Deep Reinforcement Learning.

DeepMind Control Suite Asynchronous Methods for Deep Reinforcement Learning

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:44:14.745723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:1b721ee418f3bb6b9c46a24c47427acf4e14e1a9b577b842fa333ba66e3c9a23

Observation 446edd7a-c21b-4b18-855c-86db467ad88b · outbound

This paper cites Data-efficient Deep Reinforcement Learning for Dexterous Manipulation.

DeepMind Control Suite Data-efficient Deep Reinforcement Learning for Dexterous Manipulation

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:44:14.751255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:7451930eddc180109d34557dff1a73472d2138cb5d75864dd7437d199b9e0813

Observation 0815a571-6fdf-45c5-9891-89fcae920a79 · outbound

This paper cites Prioritized Experience Replay.

DeepMind Control Suite Prioritized Experience Replay

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:44:14.756533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:8d51808d28999d675f7920f25900c109fafe29748a50d7d498a8e98b4f4f65c7

Observation 704f26a3-6e1c-4c1a-9898-d80878ae1136 · outbound

This paper cites Synthesis and stabilization of complex be- haviors through online trajectory optimization.

DeepMind Control Suite Synthesis and stabilization of complex be- haviors through online trajectory optimization

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T07:44:14.792796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:f46642419f8acd078289918775e54f1d3790377bbeb5f08a15ead9114d6aa97a

Observation dfba87fe-73f8-49e7-98a2-7f469ab8dc87 · outbound

This paper cites Mujoco: A physics engine for model- based control.

DeepMind Control Suite Mujoco: A physics engine for model- based control

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-13T07:44:14.788345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T07:44:14.707183Z digest=sha256:dfda773837601aa7a769f4c2c6151bae68eaf98dded63735fa3d1ae68ca14254

Pith citing papers

Observation 1da3fe04-a7a1-4e8c-96dd-3207e1013801 · inbound

Continual Reinforcement Learning with Diversity Exploration and Adversarial Self-Correction cites this paper.

Continual Reinforcement Learning with Diversity Exploration and Adversarial Self-Correction DeepMind Control Suite

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-05-25T19:06:08.937336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-25T19:05:13.780087Z digest=sha256:7a3719294e9c2662304a681b63c976b690e23a97384951329eb23de83b429078

Observation aee1c70b-09af-465f-9667-305e16b3d165 · inbound

Benchmarking Model-Based Reinforcement Learning cites this paper.

Benchmarking Model-Based Reinforcement Learning DeepMind Control Suite

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-05-25T10:15:37.042559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-25T10:12:49.348162Z digest=sha256:293c188fe30766e99ffdbb362d8b64a5c3cde5d94a10dd57f2a067c0a0811c28

Observation e8a13acc-cb8d-414c-87af-0aa75e403a70 · inbound

An Actor-Critic-Attention Mechanism for Deep Reinforcement Learning in Multi-view Environments cites this paper.

An Actor-Critic-Attention Mechanism for Deep Reinforcement Learning in Multi-view Environments DeepMind Control Suite

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-05-24T19:04:50.242354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-24T19:00:33.771787Z digest=sha256:438fb556ea136aa44b08e6a84c1478c9b7b510df8da76cda459a34fa95e0b732

Observation 16d83a09-8b7e-4ce8-9dcd-8ab0ea9f3f65 · inbound

Arena: a toolkit for Multi-Agent Reinforcement Learning cites this paper.

Arena: a toolkit for Multi-Agent Reinforcement Learning DeepMind Control Suite

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-05-24T18:36:19.050493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-24T18:35:31.633881Z digest=sha256:b3db5be59ec06c1a4fba5ac619573208255a799a699a0e6a5debd22517577f5f

Observation 8cbcd9de-289e-4009-88b3-7c1f6ddde25f · inbound

DoorGym: A Scalable Door Opening Environment And Baseline Agent cites this paper.

DoorGym: A Scalable Door Opening Environment And Baseline Agent DeepMind Control Suite

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-14T15:04:02.371845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:04:02.371845Z digest=sha256:a6a26d41f7500143efec5b0b5184573d9030e71f4c02123b14fa1ff8be250cb2

Observation eeab421e-c2d9-4e84-9da8-1404c2f0436f · inbound

Behaviour Suite for Reinforcement Learning cites this paper.

Behaviour Suite for Reinforcement Learning DeepMind Control Suite

Reference 2009

Resolution
unresolved
no resolver link, observed 2026-08-14T14:20:23.242776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:20:23.242776Z digest=sha256:7ea2b3a6d46964abc62ac47a4e108237898ad83367e8b4a17c39b6b42720cef3

Observation fce1452b-b1f0-4404-8e40-74b21e56e207 · inbound

Continuous Control for High-Dimensional State Spaces: An Interactive Learning Approach cites this paper.

Continuous Control for High-Dimensional State Spaces: An Interactive Learning Approach DeepMind Control Suite

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-14T13:22:25.609678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:22:25.609678Z digest=sha256:c6cdf08c1de3efd39742a763dce75cf8de0f06ba23ab6838fc4341fb61d2f555

Observation bbf5f46a-224b-4cc9-9304-429984598fb9 · inbound

Dynamics-aware Embeddings cites this paper.

Dynamics-aware Embeddings DeepMind Control Suite

Reference 1999

Resolution
unresolved
no resolver link, observed 2026-08-14T11:20:28.277370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:20:28.277370Z digest=sha256:d486ca5a48b4f3897f4e3c3d87abcc5c8a0691fa4ef8b7d2558d592a2d1e85b6

Observation bd1a0bee-e734-4c36-bf31-d8d88a866bea · inbound

Constraint Learning for Control Tasks with Limited Duration Barrier Functions cites this paper.

Constraint Learning for Control Tasks with Limited Duration Barrier Functions DeepMind Control Suite

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-14T11:14:41.822364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:14:41.822364Z digest=sha256:d821705d64112667b1167a25ace1b4e385906cf502af7c72eac3ecfd180c9027

Observation d999fd21-c414-4317-8ded-21298ed57e68 · inbound

Exploration-Enhanced POLITEX cites this paper.

Exploration-Enhanced POLITEX DeepMind Control Suite

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-14T10:49:33.146230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:49:33.146230Z digest=sha256:c780bd23ac6def1def05f25795c5b6447db3e01776462a14d77ad6e5733ac686

Observation 88e64274-e44b-4b18-809c-bffb6c53e312 · inbound

Evolutionary reinforcement learning of dynamical large deviations cites this paper.

Evolutionary reinforcement learning of dynamical large deviations DeepMind Control Suite

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-14T05:43:41.468681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T05:43:41.468681Z digest=sha256:6c7c7adc4ac63bbaf29ff2ca683d8b230d4902ea8dcfd8249caf5c195fd47412

Observation 2107af0d-8c8b-4f7b-a27d-5b7f95de44fa · inbound

Dream to Control: Learning Behaviors by Latent Imagination cites this paper.

Dream to Control: Learning Behaviors by Latent Imagination DeepMind Control Suite

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:44:14.794093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T01:16:36.399272Z digest=sha256:9aee1aed3aff78d496b2e04c5a57adf6417bea05db2c20e26f78aef95b2613f0

Observation 6571296c-dd51-420b-9669-e171941ef493 · inbound

A Generalist Agent cites this paper.

A Generalist Agent DeepMind Control Suite

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:44:14.794093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T06:24:49.833638Z digest=sha256:fee2b7187ba6a28bc4e0e2c58c353887b4baf983d43059320041bd1d61bf0158

Observation bf152135-6bf3-4b22-ad38-7a6f5f8116c5 · inbound

Mastering Diverse Domains through World Models cites this paper.

Mastering Diverse Domains through World Models DeepMind Control Suite

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:44:14.794093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-11T09:08:21.677362Z digest=sha256:21b8d5335657c1a7b79652195c4c33590d0280fb3262d7aab25b9648aeb99210

Observation a86d6b53-1fe0-464b-8612-2f61151fa780 · inbound

Learning Interactive Real-World Simulators cites this paper.

Learning Interactive Real-World Simulators DeepMind Control Suite

Reference 149

Resolution
metadata mismatch
local_arxiv, observed 2026-05-16T02:15:18.430063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-16T02:15:18.265190Z digest=sha256:2ae719856d5c6f0a02105c214d69de2e1d374e9f86bb32705b1e06b0c83eefb5

Observation b8715765-dea1-4596-84ed-0c0a23154d20 · inbound

BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation cites this paper.

BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation DeepMind Control Suite

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-05-16T23:38:00.762837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-16T23:38:00.611856Z digest=sha256:3cb8b95380028293846f13cc160b072cb17d7e48b3be0232304bc20f57765df5

Observation 204c8b6d-ebef-4c13-a9ed-afd580d1965b · inbound

A Survey on Vision-Language-Action Models for Embodied AI cites this paper.

A Survey on Vision-Language-Action Models for Embodied AI DeepMind Control Suite

Reference 191

Resolution
verified exact
local_arxiv, observed 2026-05-24T01:25:54.412825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-24T01:25:10.150459Z digest=sha256:4aa50d7ed1990cfd9ceb4ba671483717d2e110297af8d25214a40b7fbd601adf

Observation c13aac80-e2f4-463e-b2eb-7818c171ad2e · inbound

Plasticity Loss in Deep Reinforcement Learning: A Survey cites this paper.

Plasticity Loss in Deep Reinforcement Learning: A Survey DeepMind Control Suite

Reference 101

Resolution
metadata mismatch
local_arxiv, observed 2026-05-23T18:03:18.176824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-23T18:02:30.199552Z digest=sha256:69368635555969842f04863ad35e7a2704a3402c9edafb812278f497885eef4c

Observation 3b40c114-ac46-4e80-85c3-e0ecafcdfb9c · inbound

DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning cites this paper.

DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning DeepMind Control Suite

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-05-17T16:06:09.612298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-17T16:06:09.448517Z digest=sha256:f25b1c3f68651d0b228c8a5691cfd587a090b5f49860276eca719d73559be677

Observation 1ef484d7-9a17-47bd-864c-62a0bbb620b3 · inbound

The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning cites this paper.

The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning DeepMind Control Suite

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-12T19:57:44.019548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:57:44.019548Z digest=sha256:b16e89670b0ca91647e17ddea69eeea48facd7eff47ffbecca436136c502b762

Observation a7191024-6f99-4ea4-838a-21fc4fe43c2c · inbound

A Pre-Trained Graph-Based Model for Adaptive Sequencing of Educational Documents cites this paper.

A Pre-Trained Graph-Based Model for Adaptive Sequencing of Educational Documents DeepMind Control Suite

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T18:30:34.256641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:30:34.256641Z digest=sha256:07d2e90e68623c7a72cd40afcc302c63a05d2049cadde6eca8d9671a476ab470

Observation 936a2caa-1bd3-4ba7-a870-c0edf194c34f · inbound

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement cites this paper.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement DeepMind Control Suite

Reference 35

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unresolved
no resolver link, observed 2026-08-12T12:37:10.244617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:37:10.244617Z digest=sha256:755ae563b610a1436e924595e3a8efa0975139eac44e30041bb229089e76a316

Observation 3457a125-7d69-42c0-8586-49cd62777647 · inbound

Proto Successor Measure: Representing the Behavior Space of an RL Agent cites this paper.

Proto Successor Measure: Representing the Behavior Space of an RL Agent DeepMind Control Suite

Reference 9879

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unresolved
no resolver link, observed 2026-08-12T10:20:26.688224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:20:26.688224Z digest=sha256:3a6142f68817d5507a596f18992502a9fa344eddebd56689bd56269305792454

Observation 1974da99-5b2e-4708-bdbb-e0c3cf56c6ce · inbound

Quantization-Aware Imitation-Learning for Resource-Efficient Robotic Control cites this paper.

Quantization-Aware Imitation-Learning for Resource-Efficient Robotic Control DeepMind Control Suite

Reference 42

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no resolver link, observed 2026-08-12T04:48:34.046161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:48:34.046161Z digest=sha256:320bf54faa6861cdcbd8fd287c40a4fd2f276d538e7f5d161c731b5bba12b34b

Observation 1da024ce-5f1e-4160-baa2-d27fe26bfac3 · inbound

LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations cites this paper.

LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations DeepMind Control Suite

Reference 21

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source=pdf_text observed=2026-08-12T04:25:49.858050Z digest=sha256:f8d68e5a22f7d0bb8127520ad9ced2cf50fe1c27097433e28be62824508766da

Observation 498ee4d0-47ef-408b-9e8d-d0e330dd76de · inbound

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning cites this paper.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning DeepMind Control Suite

Reference 14

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source=pdf_text observed=2026-08-11T20:28:45.020457Z digest=sha256:b7c1a77a6250b5ed32367b58b4b5b0c2a7411c1f61a1562cf766f5c8058baa0b

Observation 653571ef-1a73-4cbe-afbd-5a380cf3ba5d · inbound

MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization cites this paper.

MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization DeepMind Control Suite

Reference 82

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source=arxiv_source observed=2026-08-11T14:25:47.827741Z digest=sha256:3b228cdd7a9dae903756a659d12c115c65728ce5019847159b9d23fa4e1432b7

Observation 9a25c4a6-ea0c-43d8-aea4-07b9f4459cdd · inbound

Equivariant Action Sampling for Reinforcement Learning and Planning cites this paper.

Equivariant Action Sampling for Reinforcement Learning and Planning DeepMind Control Suite

Reference 42

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source=arxiv_source observed=2026-08-11T14:28:18.693950Z digest=sha256:b6f89636bded2e2a2ec96db94a2288f13ed1f1e904ce51ffec88c219da2d336e

Observation 60759d72-b6ed-4eb5-805d-bc931de3135f · inbound

When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning? cites this paper.

When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning? DeepMind Control Suite

Reference 43

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source=arxiv_source observed=2026-08-11T12:59:13.692376Z digest=sha256:752ca41999a8b2facb41cfc5e479c2f6e71739cd15455120f814ab634c0867d3

Observation 477d9800-9cd4-4f15-bd20-12d6563daecb · inbound

Mimicking-Bench: A Benchmark for Generalizable Humanoid-Scene Interaction Learning via Human Mimicking cites this paper.

Mimicking-Bench: A Benchmark for Generalizable Humanoid-Scene Interaction Learning via Human Mimicking DeepMind Control Suite

Reference 94

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source=pdf_text observed=2026-08-11T05:19:19.086253Z digest=sha256:b02d1fdf8ed6d71e95f860fad92e6bd176a58795019d61e231132f5d93e6c695

Observation 69f9d5b3-9ffe-4d3f-b8eb-03d142fef62d · inbound

Dream to Fly: Model-Based Reinforcement Learning for Vision-Based Drone Flight cites this paper.

Dream to Fly: Model-Based Reinforcement Learning for Vision-Based Drone Flight DeepMind Control Suite

Reference 19

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local_arxiv, observed 2026-05-23T04:55:25.139296Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-23T04:53:33.503100Z digest=sha256:208b41d5e297fa862ac0d33e2b39377cc8cc39d1e893181ea5ca2ca6edeffdde

Observation dddd86c4-1003-4c99-8cda-baba5dd184d7 · inbound

Episodic Novelty Through Temporal Distance cites this paper.

Episodic Novelty Through Temporal Distance DeepMind Control Suite

Reference 52

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source=arxiv_source observed=2026-08-10T14:25:59.006558Z digest=sha256:454706433cce61354e180b70ecb5ec63712611faedd988c724e49c0ef64116d5

Observation 03f9be27-826b-443c-bd3f-733efbb4037e · inbound

Towards General-Purpose Model-Free Reinforcement Learning cites this paper.

Towards General-Purpose Model-Free Reinforcement Learning DeepMind Control Suite

Reference 23

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source=pdf_text observed=2026-08-10T13:47:01.686537Z digest=sha256:96a8d5fdc0b580446517d2371e45d8c4100e718cd9698c5eae676e1b3b887917

Observation a101682c-8ed7-4680-83a8-a66b30983d51 · inbound

Fisher-Guided Selective Forgetting: Mitigating The Primacy Bias in Deep Reinforcement Learning cites this paper.

Fisher-Guided Selective Forgetting: Mitigating The Primacy Bias in Deep Reinforcement Learning DeepMind Control Suite

Reference 12

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source=pdf_text observed=2026-08-09T17:46:07.292556Z digest=sha256:16f3ba1cdc39231faf3899c906636f1f9bdec165e4d734e490008f06d6bb72c3

Observation 0571d6fd-0f68-4fae-ba71-14eab8a96cac · inbound

Trajectory World Models for Heterogeneous Environments cites this paper.

Trajectory World Models for Heterogeneous Environments DeepMind Control Suite

Reference 14

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source=pdf_text observed=2026-08-09T15:36:48.688461Z digest=sha256:c51d4c97f63a5fe9eb6aa99ff8194e0e6259d1dd79102fa697f4a1b44c02c801

Observation 6e2de058-a7e6-4ff0-8168-187637aace92 · inbound

Rethinking Latent Redundancy in Behavior Cloning: An Information Bottleneck Approach for Robot Manipulation cites this paper.

Rethinking Latent Redundancy in Behavior Cloning: An Information Bottleneck Approach for Robot Manipulation DeepMind Control Suite

Reference 51

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source=arxiv_source observed=2026-08-09T10:56:57.814242Z digest=sha256:423e261f562f420152623c7dbf12cc457022b41d27deb5b50c2944015c24ba8c

Observation ff320b2a-65dc-42d1-90f9-2fc5efa76819 · inbound

Domain-Invariant Per-Frame Feature Extraction for Cross-Domain Imitation Learning with Visual Observations cites this paper.

Domain-Invariant Per-Frame Feature Extraction for Cross-Domain Imitation Learning with Visual Observations DeepMind Control Suite

Reference 20

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source=pdf_text observed=2026-08-09T10:55:38.102479Z digest=sha256:bc068d2f65367084322521a79ddd149476f63541dcb1df9c2de963214d606a1a

Observation 03b7e3bf-b9ad-4a06-9d3d-d41cd7ab7fc9 · inbound

TD-M(PC)$^2$: Improving Temporal Difference MPC Through Policy Constraint cites this paper.

TD-M(PC)$^2$: Improving Temporal Difference MPC Through Policy Constraint DeepMind Control Suite

Reference 38

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source=pdf_text observed=2026-08-09T04:38:30.724743Z digest=sha256:df2d86620f1e0a5dd7b2e3f5b954a7c5459b6dbf60d40daac032a263b8210483

Observation 5ed334e7-e600-487b-823e-b0184f09bff2 · inbound

Efficient Reinforcement Learning Through Adaptively Pretrained Visual Encoder cites this paper.

Efficient Reinforcement Learning Through Adaptively Pretrained Visual Encoder DeepMind Control Suite

Reference 51

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source=arxiv_source observed=2026-08-08T18:56:45.463706Z digest=sha256:04e1b49f525bcf6bb1e04aa710c153dbaa1a19578809459a96fbcb5dbe1f5ff8

Observation d6b13d53-5601-4e40-b84a-d9868ee27780 · inbound

Skill Expansion and Composition in Parameter Space cites this paper.

Skill Expansion and Composition in Parameter Space DeepMind Control Suite

Reference 32

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source=pdf_text observed=2026-08-08T17:26:09.347625Z digest=sha256:a1f7f2b4a61d6c5a573969ef215de0c4ec5373cd140847cfb647e1d1af4a8ac3

Observation e2ce34cb-fe22-4df6-a1f3-e20a89ae72cc · inbound

DrugImproverGPT: A Large Language Model for Drug Optimization with Fine-Tuning via Structured Policy Optimization cites this paper.

DrugImproverGPT: A Large Language Model for Drug Optimization with Fine-Tuning via Structured Policy Optimization DeepMind Control Suite

Reference 69

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source=pdf_text observed=2026-08-08T13:29:10.793596Z digest=sha256:0a39ce74693e901aa59d4bffe4030927bf018fe166aa8e8208c0173303ed8400

Observation 55ee6be8-6836-40f9-a899-c5f22e3d4788 · inbound

Exploratory Diffusion Model for Unsupervised Reinforcement Learning cites this paper.

Exploratory Diffusion Model for Unsupervised Reinforcement Learning DeepMind Control Suite

Reference 58

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source=pdf_text observed=2026-08-08T13:21:18.414534Z digest=sha256:a6bee1646bfd6a3a9f0ba17776527212c6ddc1643deba37c69e934ed339da5dd

Observation 6f15bc57-ea9e-49ba-816d-260ba7d40a00 · inbound

Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization cites this paper.

Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization DeepMind Control Suite

Reference 40

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source=pdf_text observed=2026-08-08T12:32:20.124594Z digest=sha256:035b317412a5e8963586e15ef7ef55dded751a5d310a1ebdc81e3c6763671302

Observation 939260c3-2479-44fa-b1c5-9df8e07854eb · inbound

Pre-Trained Video Generative Models as World Simulators cites this paper.

Pre-Trained Video Generative Models as World Simulators DeepMind Control Suite

Reference 1998

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source=pdf_text observed=2026-08-08T15:14:22.448687Z digest=sha256:2559de90cd0abec4fc9272c5f90fe069f869aa96f2e82e415059832ba745ad03

Observation 3fe7e0bf-b594-493b-bf54-57c16464c53e · inbound

Salience-Invariant Consistent Policy Learning for Generalization in Visual Reinforcement Learning cites this paper.

Salience-Invariant Consistent Policy Learning for Generalization in Visual Reinforcement Learning DeepMind Control Suite

Reference 2018

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source=pdf_text observed=2026-08-08T05:38:20.917891Z digest=sha256:7a89fe4404b8c0a743da9a29eda906c2760e8cd4909838e6299ee786c91e5c7f

Observation 53b22708-c14d-4cac-9678-4e0d9d138082 · inbound

Learning Humanoid Standing-up Control across Diverse Postures cites this paper.

Learning Humanoid Standing-up Control across Diverse Postures DeepMind Control Suite

Reference 47

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source=pdf_text observed=2026-08-08T05:23:43.194046Z digest=sha256:5d9e5450d9419f292060dc3baf90d21c55e3c677c94c154dd76b79ffd901811f

Observation cf10259e-ff76-491c-bc8b-5636cf06afc0 · inbound

MuJoCo Playground cites this paper.

MuJoCo Playground DeepMind Control Suite

Reference 61

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source=pdf_text observed=2026-08-07T23:34:11.187882Z digest=sha256:76145fe84ad319ddec5d93a24c54327d321a9bb8b0acfb4e072570bde9d0eb91

Observation d2b0a6ae-571d-47cf-9568-3c9d58e618cf · inbound

Self-Consistent Model-based Adaptation for Visual Reinforcement Learning cites this paper.

Self-Consistent Model-based Adaptation for Visual Reinforcement Learning DeepMind Control Suite

Reference 14

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source=pdf_text observed=2026-08-07T20:08:49.580007Z digest=sha256:91f0d6ab8e0273c20b46772dfccf36e74602367939bdf67236227aa41a2a8792

Observation cf8a8f19-063d-426b-8e24-397832700133 · inbound

Causal Information Prioritization for Efficient Reinforcement Learning cites this paper.

Causal Information Prioritization for Efficient Reinforcement Learning DeepMind Control Suite

Reference 14

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source=pdf_text observed=2026-08-07T19:33:43.798577Z digest=sha256:3e4c2412435a0579f4a83750b91dfb57c79eecf94123af02ef8977a7db1a817e

Observation 2838999e-e3fd-40b8-8f79-d6fdce618c82 · inbound

Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning cites this paper.

Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning DeepMind Control Suite

Reference 34

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local_arxiv, observed 2026-05-23T00:25:14.356493Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-23T00:23:13.858606Z digest=sha256:956946f8c3dc9095375dc7fbce8dfb7c89693d15a00e4d1d4bba74389f73215f

Observation 676a07e8-6f2f-4f10-a3f3-d893aae50b66 · inbound

Solving New Tasks by Adapting Internet Video Knowledge cites this paper.

Solving New Tasks by Adapting Internet Video Knowledge DeepMind Control Suite

Reference 31

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source=arxiv_source observed=2026-08-16T11:33:00.901351Z digest=sha256:d9d2f80f5f2e7fb8843dadb6f2aaefa9cf7b349fb1517e3fad8c62c7ebf9b97e

Observation b096d802-c938-43e0-bebc-8689bfd7145c · inbound

LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities cites this paper.

LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities DeepMind Control Suite

Reference 2012

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source=pdf_text observed=2026-08-16T11:16:29.757704Z digest=sha256:ec269f583d48d6242ba06a109ab19d94563fef2738da3998f3343a5309e0532b

Observation 5eca6816-fbfc-4852-a254-0379176db644 · inbound

Q-function Decomposition with Intervention Semantics with Factored Action Spaces cites this paper.

Q-function Decomposition with Intervention Semantics with Factored Action Spaces DeepMind Control Suite

Reference 41

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source=arxiv_source observed=2026-08-16T05:16:16.574453Z digest=sha256:286fa5ea5e7141a5b0693139bc08885c729de81a9c78f8287b5b58cf16c3fe16

Observation e5e35a59-79ac-48c1-99df-a0c872ebd9c8 · inbound

Wasserstein Policy Optimization cites this paper.

Wasserstein Policy Optimization DeepMind Control Suite

Reference 46

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source=arxiv_source observed=2026-08-16T04:47:05.770349Z digest=sha256:fbf838e18dfefe4ce8cf43dfe62c6aa430ce1f4ea2afc8bd4b4452e177de5a3f

Observation 49d62347-1b97-4297-a897-17f6214a9bfe · inbound

Trajectory Entropy Reinforcement Learning for Predictable and Robust Control cites this paper.

Trajectory Entropy Reinforcement Learning for Predictable and Robust Control DeepMind Control Suite

Reference 24

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source=pdf_text observed=2026-08-15T23:40:39.938920Z digest=sha256:29ee3ad961a66b67aee9a37c8bc03d89e893d723e6a647ab877c560e58e0c897

Observation f4924f5c-39ff-4c37-8aa1-a33671b683b7 · inbound

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning cites this paper.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning DeepMind Control Suite

Reference 29

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source=pdf_text observed=2026-08-15T21:24:27.462645Z digest=sha256:4ef4d70d19b0b09f82f76625c32ea025198534f5c84da731fedcf38aa2882bdb

Observation 512581c5-0282-48d5-a51f-b5d11898a776 · inbound

Learning Diverse Natural Behaviors for Enhancing the Agility of Quadrupedal Robots cites this paper.

Learning Diverse Natural Behaviors for Enhancing the Agility of Quadrupedal Robots DeepMind Control Suite

Reference 54

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source=pdf_text observed=2026-08-15T21:26:20.023698Z digest=sha256:b6e4e49953ca443ae501dc687ecdd06cbee0d74c78ef2248c69c2d2615fc6e29

Observation 90bb5f1d-81a0-4d9e-96e5-70bce867cb92 · inbound

ImagineBench: Evaluating Reinforcement Learning with Large Language Model Rollouts cites this paper.

ImagineBench: Evaluating Reinforcement Learning with Large Language Model Rollouts DeepMind Control Suite

Reference 34

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source=arxiv_source observed=2026-08-15T21:22:16.142589Z digest=sha256:6536d68842a72a07b9a1ca2e99f020171103e83b28f64c2e72d637d33b57593f

Observation 2b3a41f8-d149-45ed-8003-3e5229198334 · inbound

Zero-Shot Visual Generalization in Robot Manipulation cites this paper.

Zero-Shot Visual Generalization in Robot Manipulation DeepMind Control Suite

Reference 46

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source=pdf_text observed=2026-08-15T20:55:25.478527Z digest=sha256:819d8bc4a5ceb50a76f03859c86eb5b5f1f8c6f4df933ac98ee3fa9658d53c8e

Observation ba82ac2c-b88e-4ebc-8a14-984b6a5dac50 · inbound

TD-GRPC: Temporal Difference Learning with Group Relative Policy Constraint for Humanoid Locomotion cites this paper.

TD-GRPC: Temporal Difference Learning with Group Relative Policy Constraint for Humanoid Locomotion DeepMind Control Suite

Reference 47

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source=pdf_text observed=2026-08-15T20:34:23.989147Z digest=sha256:7c8c3b9e51d526df838ede382a2f76f2e9257d005409159831d9c383090705a1

Observation f29855f9-5e6b-47a6-a869-b01169c27d81 · inbound

Saliency-Aware Quantized Imitation Learning for Efficient Robotic Control cites this paper.

Saliency-Aware Quantized Imitation Learning for Efficient Robotic Control DeepMind Control Suite

Reference 46

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source=pdf_text observed=2026-08-07T15:26:45.982042Z digest=sha256:dc4a8fd7ff54b0250a12ebbcdfe759d471fa5720ddb83aa97a10b169afd14f8d

Observation ea192361-4a4e-46a7-8aef-1e9982e8c62c · inbound

Maximum Total Correlation Reinforcement Learning cites this paper.

Maximum Total Correlation Reinforcement Learning DeepMind Control Suite

Reference 7

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source=pdf_text observed=2026-08-07T15:03:43.855369Z digest=sha256:da5fab6b9da362fe646693aa2ff3efb4b2075d985add1cfd21dac396aa24dd40

Observation 600fe287-358e-4acc-8640-28b23aa8ec7b · inbound

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos cites this paper.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos DeepMind Control Suite

Reference 30

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source=pdf_text observed=2026-08-07T14:31:30.854731Z digest=sha256:a509d4ef4e3518bb2ccc04929c03ffffb68e470c16ffd9e97a7bc2df5b0f1a19

Observation 91cf2336-d0c9-4b15-bfcd-b2a770fe4511 · inbound

Beyond Domain Randomization: Event-Inspired Perception for Visually Robust Adversarial Imitation from Videos cites this paper.

Beyond Domain Randomization: Event-Inspired Perception for Visually Robust Adversarial Imitation from Videos DeepMind Control Suite

Reference 9

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source=pdf_text observed=2026-08-07T14:27:30.789245Z digest=sha256:94f201820a8e012cd7a342e7e22d497b0643c30e88e9a35558f208b0b3327c9e

Observation f4797f4a-225b-42be-bab4-c83fa7fde7b1 · inbound

Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners cites this paper.

Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners DeepMind Control Suite

Reference 97

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source=pdf_text observed=2026-08-07T12:58:54.169006Z digest=sha256:4b9a3f920155f47bc181b6e60a6c1af240409b64c2c61db7d4e780a82e3f238c

Observation 2b36b0e9-bb24-401d-8b6f-dc40103a9cc9 · inbound

Mastering Massive Multi-Task Reinforcement Learning via Mixture-of-Expert Decision Transformer cites this paper.

Mastering Massive Multi-Task Reinforcement Learning via Mixture-of-Expert Decision Transformer DeepMind Control Suite

Reference 16

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source=pdf_text observed=2026-08-07T12:35:13.961550Z digest=sha256:5b4738470ac4ee4ce0273f38a92a67915647b0c61ad97e9a6bc0225f43bb510e

Observation 17e588d6-466d-4205-938a-469714d91c97 · inbound

CLARIFY: Contrastive Preference Reinforcement Learning for Untangling Ambiguous Queries cites this paper.

CLARIFY: Contrastive Preference Reinforcement Learning for Untangling Ambiguous Queries DeepMind Control Suite

Reference 37

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source=arxiv_source observed=2026-08-07T12:13:00.774609Z digest=sha256:7f2b0e4063e380b27f238754c02f90f8814df88ae55c28d569dd25f6783bed02

Observation 2bdfd756-83ac-44a5-aafa-613e25fea1e5 · inbound

Understanding Behavioral Metric Learning: A Large-Scale Study on Distracting Reinforcement Learning Environments cites this paper.

Understanding Behavioral Metric Learning: A Large-Scale Study on Distracting Reinforcement Learning Environments DeepMind Control Suite

Reference 63

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source=arxiv_source observed=2026-08-07T12:10:07.623587Z digest=sha256:1a433453886f372d90a5ca76f7772d0630d2b2172252ca2ed14eb8819d770acc

Observation 16b43741-5e71-4deb-b037-c7410b7eb4ad · inbound

Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn cites this paper.

Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn DeepMind Control Suite

Reference 17

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source=pdf_text observed=2026-08-07T12:07:25.491932Z digest=sha256:4ae2c4d4ad99122482247565b9e48b8a3940e896c6155b5e7796f438be85dfde

Observation 206a9620-d6d5-408f-9f2f-1fe6f85fa7b9 · inbound

LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model cites this paper.

LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model DeepMind Control Suite

Reference 8

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source=pdf_text observed=2026-08-07T11:46:59.223222Z digest=sha256:3944c8903ed13c7b2ca3bc592914883dad12d6021cf2d926acd5b4110ad7d9f4

Observation 74f7e137-fc3e-4938-8567-ff461be12493 · inbound

Self-Predictive Dynamics for Generalization of Vision-based Reinforcement Learning cites this paper.

Self-Predictive Dynamics for Generalization of Vision-based Reinforcement Learning DeepMind Control Suite

Reference 21

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source=pdf_text observed=2026-08-07T10:47:32.916754Z digest=sha256:a310593450890c14b24569d5870bff564edfe1f4c1216cf8dbc558cd76c07377

Observation 3669cb44-9fb7-4db1-9904-ddb582f30561 · inbound

Dream to Generalize: Zero-Shot Model-Based Reinforcement Learning for Unseen Visual Distractions cites this paper.

Dream to Generalize: Zero-Shot Model-Based Reinforcement Learning for Unseen Visual Distractions DeepMind Control Suite

Reference 35

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source=arxiv_source observed=2026-08-07T10:46:33.440488Z digest=sha256:e7f29382921eed27c8929c26decdafa4c45a61c77ab7d9d5182eaee6c272bb28

Observation 7d0962a6-04d4-4af0-ae2b-2dceeda5975d · inbound

Intention-Conditioned Flow Occupancy Models cites this paper.

Intention-Conditioned Flow Occupancy Models DeepMind Control Suite

Reference 107

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local_arxiv, observed 2026-05-19T10:27:14.584457Z

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source=pdf_text observed=2026-05-19T10:24:52.160209Z digest=sha256:3b4466bd1534b751d077d2874597ccbb5ad72c6356bb5227a6fabf7e43d2c5f8

Observation 60bf0a01-09cd-4194-869f-ddc7a0b9ec41 · inbound

An Open-Source Software Toolkit & Benchmark Suite for the Evaluation and Adaptation of Multimodal Action Models cites this paper.

An Open-Source Software Toolkit & Benchmark Suite for the Evaluation and Adaptation of Multimodal Action Models DeepMind Control Suite

Reference 27

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source=pdf_text observed=2026-08-07T04:59:41.401667Z digest=sha256:06dec26b3a0bdf19f1844feb5c7009588d49d4dfed935d4d2edb1ab0fc3dc01b

Observation 8a9c1ad1-640c-4584-826a-93eef9aba65b · inbound

Multi-Task Reward Learning from Human Ratings cites this paper.

Multi-Task Reward Learning from Human Ratings DeepMind Control Suite

Reference 11

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source=arxiv_source observed=2026-08-07T04:59:50.587696Z digest=sha256:e6c4e79ce0105d6f1591252ccadd7c9df704401f89472f7888d2d6bb5e3fb6e7

Observation 4e3cff0f-aa7f-4865-8ef2-41ca97ea3b63 · inbound

SkillBlender: Towards Versatile Humanoid Whole-Body Loco-Manipulation via Skill Blending cites this paper.

SkillBlender: Towards Versatile Humanoid Whole-Body Loco-Manipulation via Skill Blending DeepMind Control Suite

Reference 44

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source=pdf_text observed=2026-08-07T04:54:02.297439Z digest=sha256:8150b060c5e0e10b92851fc27e9e3eeeeb1a5441d13d52e038767a83bcce837c

Observation ca32db8c-638b-4247-8b9d-8dbecc0ca744 · inbound

Flow-Based Policy for Online Reinforcement Learning cites this paper.

Flow-Based Policy for Online Reinforcement Learning DeepMind Control Suite

Reference 39

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source=pdf_text observed=2026-08-15T20:13:00.369356Z digest=sha256:367ffddebe48283797b405345e2dc4959d73106b2373341ac65a8e97d060c56c

Observation 364092c5-6388-4b31-afdc-14272e675950 · inbound

The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning cites this paper.

The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning DeepMind Control Suite

Reference 57

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source=arxiv_source observed=2026-08-07T00:32:53.351761Z digest=sha256:fcd558ea200e453386a4238c9e581aab526734c2263dc541b3cf335b3697246a

Observation 8ea88ba8-32ca-403b-9456-f0b60699cb2d · inbound

PB$^2$: Preference Space Exploration via Population-Based Methods in Preference-Based Reinforcement Learning cites this paper.

PB$^2$: Preference Space Exploration via Population-Based Methods in Preference-Based Reinforcement Learning DeepMind Control Suite

Reference 36

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source=arxiv_source observed=2026-08-07T00:33:04.252878Z digest=sha256:eee1ab791c35e041c4d7616753b71d3ef96d53d8fd2d46bf17d79c3994211a8d

Observation 66b480bf-5b9a-445a-93bd-0ddbd0d3441a · inbound

Unsupervised Skill Discovery through Skill Regions Differentiation cites this paper.

Unsupervised Skill Discovery through Skill Regions Differentiation DeepMind Control Suite

Reference 55

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source=pdf_text observed=2026-08-07T00:27:00.688031Z digest=sha256:266345c245e9f80c4209cb120418ba1869b7bf9387a594f18d90dc23477812c9

Observation 2a2f8887-3798-40b0-8beb-df1ae25b0f29 · inbound

Zero-Shot Reinforcement Learning Under Partial Observability cites this paper.

Zero-Shot Reinforcement Learning Under Partial Observability DeepMind Control Suite

Reference 81

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source=arxiv_source observed=2026-08-15T19:37:29.878368Z digest=sha256:f0db96a9520577e66199656c37c6c1a7554352c53fc3256feb22c6f899812c40

Observation 884867cb-5336-4f9c-8768-509e25106d40 · inbound

Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning cites this paper.

Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning DeepMind Control Suite

Reference 56

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source=arxiv_source observed=2026-08-15T19:16:29.065972Z digest=sha256:fb2739cebaec6856f5590af99b2b665a4d2228e15cb0ddbf3c5a22e0e29e49ea

Observation c9264219-78f5-4415-86dc-f119aa5a0721 · inbound

Unsupervised Data Generation for Offline Reinforcement Learning: A Perspective from Model cites this paper.

Unsupervised Data Generation for Offline Reinforcement Learning: A Perspective from Model DeepMind Control Suite

Reference 52

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source=arxiv_source observed=2026-08-15T18:36:10.094539Z digest=sha256:d9c49d88020afd75980fcdb17f5e5db0b2ff5829dcb28f4d1906d274431c2411

Observation 69566d21-3b66-42e4-b757-8d852cfba287 · inbound

rQdia: Regularizing Q-Value Distributions With Image Augmentation cites this paper.

rQdia: Regularizing Q-Value Distributions With Image Augmentation DeepMind Control Suite

Reference 2014

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source=pdf_text observed=2026-08-06T22:30:08.646686Z digest=sha256:793ce155d1bc65f92a6ef89282ab0236826e2018c8d92017d414d6f3c1cdfd81

Observation b1f76eac-f5de-486b-a84d-587b9d6015f2 · inbound

RoboEval: Where Robotic Manipulation Meets Structured and Scalable Evaluation cites this paper.

RoboEval: Where Robotic Manipulation Meets Structured and Scalable Evaluation DeepMind Control Suite

Reference 4

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local_arxiv, observed 2026-05-19T07:22:09.348429Z

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source=pdf_text observed=2026-05-19T07:19:07.662487Z digest=sha256:7610d2434e2b2d3386e91faf84856a3e474474c829f72411cb9b01f604bd7c60

Observation f34593ff-a47b-41dd-b8a5-c7ec3e295d37 · inbound

Distributional Soft Actor-Critic with Diffusion Policy cites this paper.

Distributional Soft Actor-Critic with Diffusion Policy DeepMind Control Suite

Reference 8

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source=pdf_text observed=2026-08-06T20:59:05.188589Z digest=sha256:040ed422ad9ed818364f770d84060dcfe812f91731ffb421b4aaf02a59c9b851

Observation a3b7639b-7c2d-4fb1-9739-cf884d6fc7b2 · inbound

A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control cites this paper.

A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control DeepMind Control Suite

Reference 46

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source=arxiv_source observed=2026-08-06T20:31:07.869907Z digest=sha256:2c97477ed6bea53917ddf56453005120237dd4406241951451b3056d761ea5a1

Observation 62811960-c9fe-4002-94d9-59eee7640de7 · inbound

Epistemically-guided forward-backward exploration cites this paper.

Epistemically-guided forward-backward exploration DeepMind Control Suite

Reference 22

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source=pdf_text observed=2026-08-06T19:32:35.041566Z digest=sha256:0fabb44ead8587edc1221a4e2312206488c792dc246856dcab4364512785de8d

Observation 988eac78-cb55-455f-8fa4-138eb22a2724 · inbound

FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making cites this paper.

FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making DeepMind Control Suite

Reference 39

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source=arxiv_source observed=2026-08-06T17:12:29.950188Z digest=sha256:a12eafde12337f3dbfabbda2d099d68336aeab9adc82f6ccce582d442a0a63fc

Observation bbeeeba4-80c0-4693-9d85-79b85eef1422 · inbound

Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities cites this paper.

Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities DeepMind Control Suite

Reference 93

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source=pdf_text observed=2026-08-06T16:34:25.223363Z digest=sha256:615d57ff4175cc8aae10ba60b63fb7dc995c39fe56aa27afa8a7f4a2fa19926a

Observation 2c115efa-d84f-46cc-9419-68c1c54c748a · inbound

Balancing Expressivity and Robustness: Constrained Rational Activations for Reinforcement Learning cites this paper.

Balancing Expressivity and Robustness: Constrained Rational Activations for Reinforcement Learning DeepMind Control Suite

Reference 35

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source=arxiv_source observed=2026-08-06T15:55:36.701148Z digest=sha256:470344228ce051a1570c56fb4291f090a45155c42dafa8f29d974f6c99746a85

Observation f4537ca1-3755-46b8-9780-389e03224349 · inbound

Flow Matching Policy Gradients cites this paper.

Flow Matching Policy Gradients DeepMind Control Suite

Reference 69

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source=pdf_text observed=2026-08-06T13:07:09.689388Z digest=sha256:4af1db75389dc87edf68b0a9a92a9e865d3c7ae1d4c4ebb9c512414e9c8f18a2

Observation 68c89edc-604f-4cc5-9864-f4518319b735 · inbound

Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks cites this paper.

Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks DeepMind Control Suite

Reference 63

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source=arxiv_source observed=2026-08-06T11:03:30.405738Z digest=sha256:93639743dbb79eeb973e47e9140c58dffb58cce0491d65c106579874b8173d49

Observation 5a627790-67da-4c89-ad59-60d9bc95771b · inbound

Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies cites this paper.

Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies DeepMind Control Suite

Reference 48

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source=pdf_text observed=2026-08-06T04:39:07.992274Z digest=sha256:ba7fd9e8dc3804503d71c8a79f200563cceb18a242d15bb8244b6c8d2645d0b0

Observation 671c5a40-c46a-437c-bf47-dbadb5d87f7f · inbound

Robust Remote Reinforcement Learning over Unreliable Communication Channels using Homomorphic State Encoding cites this paper.

Robust Remote Reinforcement Learning over Unreliable Communication Channels using Homomorphic State Encoding DeepMind Control Suite

Reference 39

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local_arxiv, observed 2026-05-19T00:02:54.137961Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-19T00:02:34.789456Z digest=sha256:07ce34b40fca3e3dfed5d1f0dfb6f7d5dcc60e457ef3bad4e55186d4289b995d

Observation 41275ee9-78e0-4b8f-900f-bd5c02bcc698 · inbound

Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges cites this paper.

Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges DeepMind Control Suite

Reference 106

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source=pdf_text observed=2026-08-05T21:02:04.475954Z digest=sha256:70e5f94622272067619b66e93f274720e66035a431f388b9e0d94214dda46618

Observation b7c63e72-f786-46c6-b334-0d12c0924c5c · inbound

Arnold: a generalist muscle transformer policy cites this paper.

Arnold: a generalist muscle transformer policy DeepMind Control Suite

Reference 1

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source=pdf_text observed=2026-08-05T16:41:53.442877Z digest=sha256:90e27d9c40a33221b8b00590e547ce901bbc1e7b0e351724607e158eb3322331

Observation f64fb178-d907-4734-a8d3-54012a4eafb9 · inbound

Use the Online Network If You Can: Towards Fast and Stable Reinforcement Learning cites this paper.

Use the Online Network If You Can: Towards Fast and Stable Reinforcement Learning DeepMind Control Suite

Reference 9

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local_arxiv, observed 2026-05-21T21:34:22.305967Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-21T21:33:40.229376Z digest=sha256:221373613b637cd855fe625e1236c568725bd0a790505130effa9ad80f152ea1

Observation 6b28899f-3b84-4e68-9dde-d8958becdc0e · inbound

D2 Actor Critic: Diffusion Actor Meets Distributional Critic cites this paper.

D2 Actor Critic: Diffusion Actor Meets Distributional Critic DeepMind Control Suite

Reference 32

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local_arxiv, observed 2026-05-25T07:35:29.478495Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-25T07:31:27.330951Z digest=sha256:fbe5603fde3b1352ce73758322396d777792086e68062fd680a00ed36c555859

Observation 8fc0e4de-9b14-4c3c-966c-2eb11a5a805c · inbound

PAC-Bayesian Reinforcement Learning Trains Generalizable Policies cites this paper.

PAC-Bayesian Reinforcement Learning Trains Generalizable Policies DeepMind Control Suite

Reference 30

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source=arxiv_source observed=2026-08-04T10:24:38.082720Z digest=sha256:e8fcba7ade0bdb4a0786f802bfa20461cd1d8fbc0b38920bdbd7a75483698a59