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Paper Citation Record · LEDGER

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning

As of 19 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 2 inbound Pith citation observations for arXiv:2505.03172.

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

pith.paper-citation-record.v1
2505.03172 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:02:25.268972Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T19:24:48.899301Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:17:57.466822Z

Reference resolution

56 of 56 outbound references displayed

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  • verified fuzzy20
  • unresolved34
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation de6667e7-e93d-4165-939d-cf26975d4f22 · outbound

This paper cites write newline.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning write newline

Reference 1

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Unavailable: canonical work link unavailable.

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Observation aaf233bf-ed7f-489c-9693-4f304d4a8890 · outbound

This paper cites f-policy gradients: A general framework for goal-conditioned rl using f-divergences.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning f-policy gradients: A general framework for goal-conditioned rl using f-divergences

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 1c2b49ea-3dbd-403a-a73d-6ec5d2cac94a · outbound

This paper cites Hindsight experience replay.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Hindsight experience replay

Reference 3

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Observation 497559a4-9810-4424-85fc-a60e506f6a78 · outbound

This paper cites Addressing hindsight bias in multigoal reinforcement learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Addressing hindsight bias in multigoal reinforcement learning

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8cf70840-a663-42f3-a81e-9eb18edec4ca · outbound

This paper cites Causal sufficiency and actual causation.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Causal sufficiency and actual causation

Reference 6

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Source-reported events for the cited work

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Observation d9b65a1e-9b31-4ab0-84f9-c7e0b81904c8 · outbound

This paper cites Context-Specific Independence in Bayesian Networks.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Context-Specific Independence in Bayesian Networks

Reference 7

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local_arxiv, observed 2026-08-16T00:02:25.774506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ea98d967-7b78-40d3-bb19-480c09067b4d · outbound

This paper cites Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search

Reference 8

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source=arxiv_source observed=2026-08-16T00:02:24.946891Z digest=sha256:eedb11ebae2ad9fe172e2fdc4261516b90c6f39aeaa186dec1ee14016a8d9402

Observation 6b00cb03-36e2-4c9f-b0c3-ae3ea758f87c · outbound

This paper cites Goal-conditioned reinforcement learning with imagined subgoals.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Goal-conditioned reinforcement learning with imagined subgoals

Reference 9

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source=arxiv_source observed=2026-08-16T00:02:24.954473Z digest=sha256:875408dc03aeda051d0353294fb853f3a9693947f4d380e4209a566122fc60c1

Observation e2f64428-e9f8-4850-a6a0-8d3ef6b2e09e · outbound

This paper cites Hypothesis-driven skill discovery for hierarchical deep reinforcement learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Hypothesis-driven skill discovery for hierarchical deep reinforcement learning

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation a4c09fbe-3bdd-4baa-81cc-c63ed4e91e9c · outbound

This paper cites Granger Causal Interaction Skill Chains.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Granger Causal Interaction Skill Chains

Reference 11

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Observation 347c151f-ea00-4823-8b1f-b36e9d55d65a · outbound

This paper cites Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning

Reference 12

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Observation e14721c9-eac5-404e-be67-44a32ceb19f5 · outbound

This paper cites Automated Discovery of Functional Actual Causes in Complex Environments.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Automated Discovery of Functional Actual Causes in Complex Environments

Reference 13

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Observation b89904c0-198e-4a33-bacd-6cfcf916570f · outbound

This paper cites Curriculum-guided hindsight experience replay.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Curriculum-guided hindsight experience replay

Reference 14

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no resolver link, observed 2026-08-16T00:02:24.980431Z

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Unavailable: canonical work link unavailable.

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Observation 901e6cd5-7640-4c2d-8f7a-9d64bbc02f08 · outbound

This paper cites Learning dynamic attribute-factored world models for efficient multi-object reinforcement learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Learning dynamic attribute-factored world models for efficient multi-object reinforcement learning

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 33454f7b-fb16-42d7-8369-32512884e7bb · outbound

This paper cites Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 11573ea3-6cae-465f-b17b-fa77e955c625 · outbound

This paper cites Actual causality.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Actual causality

Reference 17

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Observation 1fe0ca21-43b8-47bf-ab36-7d506e0cabc1 · outbound

This paper cites On discovery of local independence over continuous variables via neural contextual decomposition.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning On discovery of local independence over continuous variables via neural contextual decomposition

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 7cb131d4-bb69-4184-8b2f-cb81319c0a60 · outbound

This paper cites Learning to achieve goals.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Learning to achieve goals

Reference 19

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Observation 64188320-6b22-498b-a0d5-fddf62337026 · outbound

This paper cites Efficient reinforcement learning in factored mdps.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Efficient reinforcement learning in factored mdps

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation b736f29e-43fa-49e3-a952-8c7579c6b737 · outbound

This paper cites What can i do here? learning new skills by imagining visual affordances.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning What can i do here? learning new skills by imagining visual affordances

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 08c0191a-3917-4590-aedf-585cac56f6bd · outbound

This paper cites Auto-Encoding Variational Bayes.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Auto-Encoding Variational Bayes

Reference 22

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Observation eaba6b82-8999-4235-af03-402bbeb4dc9f · outbound

This paper cites Kipf and Max Welling.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Kipf and Max Welling

Reference 23

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source=arxiv_source observed=2026-08-16T00:02:25.031963Z digest=sha256:ce9497af935fbe26353ab1c0d16710b3a1b877a9b78799151e5369b01c7a5091

Observation ec83703a-3704-4f1f-ac43-febae58e29ea · outbound

This paper cites ARCHER: Aggressive Rewards to Counter bias in Hindsight Experience Replay.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning ARCHER: Aggressive Rewards to Counter bias in Hindsight Experience Replay

Reference 24

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Observation 8c6db143-3ac0-48c4-8935-75f18d73d6a2 · outbound

This paper cites Generalized hindsight for reinforcement learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Generalized hindsight for reinforcement learning

Reference 25

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T00:02:25.050032Z digest=sha256:fe23bc84948247eca95f47c73dd4bb59ec4785c022abd1776933b409eb840930

Observation d8eabd5f-6da3-4de4-8012-715d8c3d65be · outbound

This paper cites Continuous control with deep reinforcement learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Continuous control with deep reinforcement learning

Reference 26

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source=arxiv_source observed=2026-08-16T00:02:25.056399Z digest=sha256:7ab0aa1dc293a2c6e57bd0ea1a269bfd597e5995e3dd0db0de5c7f0940d02868

Observation 083a4f31-92d2-467e-997a-3848e65441e2 · outbound

This paper cites Biscuit: Causal representation learning from binary interactions.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Biscuit: Causal representation learning from binary interactions

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f56e2e25-3703-468f-8073-2fc7b8334295 · outbound

This paper cites Goal-conditioned reinforcement learning: Problems and solutions.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Goal-conditioned reinforcement learning: Problems and solutions

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 555f929e-1d8c-490b-9fa8-e45597252d4f · outbound

This paper cites Physgen: Rigid-body physics-grounded image-to-video generation.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Physgen: Rigid-body physics-grounded image-to-video generation

Reference 29

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T00:02:25.073188Z digest=sha256:61d87d16789605160ee874d0021168a0ab9843982bada9558849affa2638e832

Observation 8037f7f6-1063-421e-a8dd-7364ef221da9 · outbound

This paper cites Offline goal-conditioned reinforcement learning via f -advantage regression.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Offline goal-conditioned reinforcement learning via f -advantage regression

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f06681ba-d77f-4a70-af52-7756408c7417 · outbound

This paper cites Localizing external contact using proprioceptive sensors: The contact particle filter.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Localizing external contact using proprioceptive sensors: The contact particle filter

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T00:02:25.088740Z digest=sha256:2fcf81a2af773df32f8959f4e0705d4adee46e4f5f369fd6d63ff290c68f4b14

Observation 4b96771a-884f-41a5-b09f-60736a0b059e · outbound

This paper cites Visual reinforcement learning with imagined goals.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Visual reinforcement learning with imagined goals

Reference 32

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source=arxiv_source observed=2026-08-16T00:02:25.093915Z digest=sha256:2aa8c766be3c8c024048287906e35cca54695149054954d57e94be0b3d3d1983

Observation 4c52e925-0e37-491a-af7d-ad9ceca80905 · outbound

This paper cites Causality.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Causality

Reference 33

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:02:25.099785Z digest=sha256:1b2d72225c143068cbd87852d9032bafb9fbe90102f033ddf271f55319e5dd14

Observation d84bafcf-d95c-4be6-9b24-5ff82f80e882 · outbound

This paper cites Counterfactual data augmentation using locally factored dynamics.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Counterfactual data augmentation using locally factored dynamics

Reference 34

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raw_fallback, observed 2026-08-16T00:02:26.076691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T00:02:25.104966Z digest=sha256:eb19e8c807b8d2d9987e202a219b0b5ad40c724ca0e121c384629bfaa6c07ae6

Observation 1d96526e-bb26-4d23-ad12-ff9b3663c434 · outbound

This paper cites Mocoda: Model-based counterfactual data augmentation.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Mocoda: Model-based counterfactual data augmentation

Reference 35

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:02:25.116309Z digest=sha256:43393102965623e974f6a36d0dda35345954f2e8e099257cf2a0c5f95b7d7b5f

Observation e28dce80-3ce6-4c9b-a68e-26866d0816f1 · outbound

This paper cites Markov decision processes.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Markov decision processes

Reference 36

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source=arxiv_source observed=2026-08-16T00:02:25.121572Z digest=sha256:b07b6da32aca5394803e5db4ac80721bd090d29706a15485bc8044167bb80285

Observation 117f1dbd-9441-4200-82cf-ced734e30d91 · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 37

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:02:25.126440Z digest=sha256:2cfe08f9eea7e56f680ab025d0a2aad3941b744769fb6f2c45de91565cc3a206

Observation 11b11c4f-3665-4f2b-9cf4-3a7e8eaeaf13 · outbound

This paper cites The graph neural network model.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning The graph neural network model

Reference 38

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source=arxiv_source observed=2026-08-16T00:02:25.131560Z digest=sha256:6c959214d282531759c4ce0464f42ba019ea20ac03aabca8bc20c80b37561c87

Observation 84dba734-a45f-4546-962b-d469b55778ba · outbound

This paper cites Prioritized Experience Replay.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Prioritized Experience Replay

Reference 39

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no resolver link, observed 2026-08-16T00:02:25.143483Z

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source=arxiv_source observed=2026-08-16T00:02:25.143483Z digest=sha256:08967e188e2bc4087a9d6370d23a69014dbb97fc6065630af2a313bef8833139

Observation 02fcd7de-b522-435c-a793-75cdde9175aa · outbound

This paper cites Causal influence detection for improving efficiency in reinforcement learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Causal influence detection for improving efficiency in reinforcement learning

Reference 40

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source=arxiv_source observed=2026-08-16T00:02:25.152826Z digest=sha256:a6906925f78525e2b1f481c5d846b16690cfd49c51c7493553a9edba8e0e4770

Observation bec3d182-b5fc-419f-b86a-d48ec9c88165 · outbound

This paper cites Smore: Score models for offline goal-conditioned reinforcement learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Smore: Score models for offline goal-conditioned reinforcement learning

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-16T00:02:25.983311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T00:02:25.159468Z digest=sha256:87f8c1342046b21524c54f3d334df1e41f3cd14bd3204b8bbc1a6dc37f2c5572

Observation e9dcec3e-b5cf-4566-a532-c35284aee9c5 · outbound

This paper cites Score models for offline goal-conditioned reinforcement learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Score models for offline goal-conditioned reinforcement learning

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-16T00:02:25.964040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T00:02:25.166116Z digest=sha256:2e91c481fc00b1ccf0d3c99e94dbcd0d4f9598b1ff3aad2c4c3239f41ad1c010

Observation aff5685e-73cb-454f-b8d7-8c97effb158a · outbound

This paper cites A general reinforcement learning algorithm that masters chess, shogi, and go through self-play.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning A general reinforcement learning algorithm that masters chess, shogi, and go through self-play

Reference 43

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source=arxiv_source observed=2026-08-16T00:02:25.174953Z digest=sha256:6ae769adb7920a6a283b7c4861154cd04fa2fe8004ed03c24db81e864309d1c0

Observation 891fbc53-ae02-419c-9758-ce37d2ec00d4 · outbound

This paper cites Solving olympiad geometry without human demonstrations.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Solving olympiad geometry without human demonstrations

Reference 44

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source=arxiv_source observed=2026-08-16T00:02:25.180306Z digest=sha256:e27620212a3d9e79f3d2d31b72d61d56da69fad1a82180bd232f46a778936aaa

Observation 4c7f8914-8684-4053-8bb2-873979bda6a2 · outbound

This paper cites Causal Action Influence Aware Counterfactual Data Augmentation.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Causal Action Influence Aware Counterfactual Data Augmentation

Reference 45

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no resolver link, observed 2026-08-16T00:02:25.185951Z

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source=arxiv_source observed=2026-08-16T00:02:25.185951Z digest=sha256:3c44db8a106e545282cb69da294f32190503192d3e0f037d3437d8cd360b9bb1

Observation 3c9694a1-6e85-4b2f-b5a1-3c054f8ce88c · outbound

This paper cites Attention is all you need.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Attention is all you need

Reference 46

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no resolver link, observed 2026-08-16T00:02:25.192053Z

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source=arxiv_source observed=2026-08-16T00:02:25.192053Z digest=sha256:dedc5fcdc703a0887506527d41f4fae953f1294f9aee3d2ab7b7bb57fbcd7b0a

Observation d4bac299-5dae-44a9-9cd8-b16f77860cc3 · outbound

This paper cites Causal Dynamics Learning for Task-Independent State Abstraction.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Causal Dynamics Learning for Task-Independent State Abstraction

Reference 47

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no resolver link, observed 2026-08-16T00:02:25.200321Z

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source=arxiv_source observed=2026-08-16T00:02:25.200321Z digest=sha256:a12c6eea2259d27b35f1108e5fdfad6e0fc02ab5f9d4cbad92c9e7da17ac25aa

Observation a80bbe70-abd3-4c69-9ab0-402f937277ea · outbound

This paper cites Elden: Exploration via local dependencies.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Elden: Exploration via local dependencies

Reference 48

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raw_fallback, observed 2026-08-16T00:02:25.902091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T00:02:25.205055Z digest=sha256:f133f6996096342f60ab747d87c97e2596d3392adbb13041dfc7c8fdac1376bd

Observation 4f4e152f-e565-4ec5-9e26-7d537ab0056c · outbound

This paper cites COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration

Reference 49

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no resolver link, observed 2026-08-16T00:02:25.212560Z

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source=arxiv_source observed=2026-08-16T00:02:25.212560Z digest=sha256:9eb52599f9e92257ee1888ccf91dae2bd56c3b383f7f322846b94e1e402aa24e

Observation 042e9aa3-1da7-4197-a4c8-5476fce69c01 · outbound

This paper cites Outracing champion gran turismo drivers with deep reinforcement learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Outracing champion gran turismo drivers with deep reinforcement learning

Reference 50

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no resolver link, observed 2026-08-16T00:02:25.219170Z

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source=arxiv_source observed=2026-08-16T00:02:25.219170Z digest=sha256:26bfa495754eab30d1404e6a640c0dae5b02adf06776a298055cd7d4968a9f0c

Observation 9c04bc77-5ad6-483b-ae2e-7c6af0732dfe · outbound

This paper cites Curiosity-Driven Experience Prioritization via Density Estimation.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Curiosity-Driven Experience Prioritization via Density Estimation

Reference 51

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source=arxiv_source observed=2026-08-16T00:02:25.226592Z digest=sha256:4eb13dc5c27d91a63b3c80c177f1f16bbf5feb5bfc0cf80fe7325910984d03e3

Observation 85a1196c-7b75-47d1-b2b8-eaf8cdba2867 · outbound

This paper cites Maximum entropy-regularized multi-goal reinforcement learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Maximum entropy-regularized multi-goal reinforcement learning

Reference 52

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verified fuzzy
raw_fallback, observed 2026-08-16T00:02:25.879303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T00:02:25.234966Z digest=sha256:711de54fbe2acc549f6e127aa824b2e8c39132455aedcda7e3463435b1dfc248

Observation a930b131-6e99-4118-b918-6fc59d69e033 · outbound

This paper cites How does goal relabeling improve sample efficiency? In Forty-first International Conference on Machine Learning, 2024.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning How does goal relabeling improve sample efficiency? In Forty-first International Conference on Machine Learning, 2024

Reference 53

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raw_fallback, observed 2026-08-16T00:02:25.861404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T00:02:25.240414Z digest=sha256:5d0cfee6b68371620e573f22b00470c0341bacf7d213b527582b840c78005b61

Observation 2c4382d2-cbca-406f-af04-dc7c68dbf861 · outbound

This paper cites robosuite: A Modular Simulation Framework and Benchmark for Robot Learning.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning robosuite: A Modular Simulation Framework and Benchmark for Robot Learning

Reference 54

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no resolver link, observed 2026-08-16T00:02:25.246913Z

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source=arxiv_source observed=2026-08-16T00:02:25.246913Z digest=sha256:94e6c81f2f881788fa2757ec89e9fc1bc24117746d4f0175f7e587bec50f4bfa

Observation 5ab8f9aa-2e65-4e48-a791-8e9435aa32e6 · outbound

This paper cites @esa (Ref.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning @esa (Ref

Reference 55

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source=arxiv_source observed=2026-08-16T00:02:25.255816Z digest=sha256:3053bb5e2549b8908ea71c0330a8f47c8a71bdb2f7b424c3d53be486722c8aa1

Observation 5b1e1e92-0ad5-4bae-a639-a9de573b3632 · outbound

This paper cites an unresolved cited work.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Unresolved cited work

Reference 56

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no resolver link, observed 2026-08-16T00:02:25.263362Z

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source=arxiv_source observed=2026-08-16T00:02:25.263362Z digest=sha256:1485f5a4c52e7e8136a301a66f0fd78ca208e76ccd731ce541d548aa933edae6

Observation 9453b88d-3fba-4aaa-8122-965978f53a6b · outbound

This paper cites CoPhy: Counterfactual Learning of Physical Dynamics.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning CoPhy: Counterfactual Learning of Physical Dynamics

Reference 57

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source=arxiv_source observed=2026-08-16T00:02:25.268972Z digest=sha256:2ad3f675352df4179b639db2b42dc0829573191ec4b08fad8fd31dea48c98932

Pith citing papers

Observation bff3c7ac-d901-474e-ae20-3a9ccb9cd32b · inbound

Learning Object Manipulation from Scratch via Contrastive Interaction cites this paper.

Learning Object Manipulation from Scratch via Contrastive Interaction Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning

Reference 19

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arxiv_id, observed 2026-07-03T10:17:57.468138Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-27T10:10:21.427118Z digest=sha256:5f40c0beee2e07a6308b8d49a7600915770fbe0f11e09c395d321a755c480af8

Observation 025d3946-0f75-4394-ad5f-2c47d0b01249 · inbound

Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling cites this paper.

Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning

Reference 128

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no resolver link, observed 2026-07-11T19:24:48.899301Z

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source=arxiv_source observed=2026-07-11T19:24:48.899301Z digest=sha256:abe77a7a88482c90805739bc5fa38cbf766e64797204915ac121dcba362b4b9d