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Paper Citation Record · LEDGER

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces

As of 24 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 0 inbound Pith citation observations for arXiv:2411.11088.

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

pith.paper-citation-record.v1
2411.11088 v1

Coverage vector

measured 71 of 71 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:03:10.619048Z

measured 71 of 71 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

71 of 71 outbound references displayed

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  • verified fuzzy50
  • unresolved19
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 749f8502-9f40-4b75-94d9-ed3dc1a3c397 · outbound

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

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Uncertainty-based offline reinforcement learning with diversified Q-ensemble

Reference 1

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Observation b0468006-ef01-40d3-bfcc-e6608cdfc0dc · outbound

This paper cites Model-based offline planning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Model-based offline planning

Reference 2

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

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Observation b159359b-d497-4700-9b0a-500157e7a330 · outbound

This paper cites Pessimistic bootstrapping for uncertainty-driven offline reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Pessimistic bootstrapping for uncertainty-driven offline reinforcement learning

Reference 3

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Observation f582a85d-8be9-4099-b0a9-db6f6e72ab3c · outbound

This paper cites Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning

Reference 4

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Source-reported events for the cited work

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Observation 25a72a6c-9575-47ed-96c4-ac7c1494c0b7 · outbound

This paper cites Offline RL without off-policy evaluation.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Offline RL without off-policy evaluation

Reference 5

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Observation d58fc196-dfd1-4c73-b7ab-7c2425323345 · outbound

This paper cites Learning action representations for reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Learning action representations for reinforcement learning

Reference 6

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Source-reported events for the cited work

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Observation 857b78a9-c946-4d05-ad18-88788133b6e8 · outbound

This paper cites Q-transformer: Scalable offline reinforcement learning via autoregressive Q-functions.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Q-transformer: Scalable offline reinforcement learning via autoregressive Q-functions

Reference 7

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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.

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Observation 021440f1-7db9-4e6d-8e49-8fd512a8aac0 · outbound

This paper cites The dynamics of reinforcement learning in cooperative multiagent systems.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces The dynamics of reinforcement learning in cooperative multiagent systems

Reference 8

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Source-reported events for the cited work

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Observation 6b3a75aa-9c8d-4287-9ec4-cc90a1b104ea · outbound

This paper cites Deep visual reasoning - learning to predict action sequences for assembly tasks.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Deep visual reasoning - learning to predict action sequences for assembly tasks

Reference 9

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Source-reported events for the cited work

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Observation 74fd7b69-67ef-4b26-91b4-d6e56da46dcf · outbound

This paper cites Value function factorization with dynamic weighting for deep multi-agent reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Value function factorization with dynamic weighting for deep multi-agent reinforcement learning

Reference 10

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Source-reported events for the cited work

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Observation bd86cd62-fd5d-4cf3-9bf3-a3965773e0da · outbound

This paper cites Deep Reinforcement Learning in Large Discrete Action Spaces.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Deep Reinforcement Learning in Large Discrete Action Spaces

Reference 11

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Observation dfdd3a67-a0fa-4438-a90f-123165eeacc2 · outbound

This paper cites Growing action spaces.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Growing action spaces

Reference 12

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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.

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Observation 87abe69c-51b6-4503-9b57-2b0ae7c081f2 · outbound

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

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Reference 13

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Observation 6bbf57ef-247e-4efc-b255-30c90bb31930 · outbound

This paper cites A minimalist approach to offline reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces A minimalist approach to offline reinforcement learning

Reference 14

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Source-reported events for the cited work

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Observation a1bb01bb-442b-4914-b687-e5edcb645c1a · outbound

This paper cites Addressing function approximation error in actor-critic methods.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Addressing function approximation error in actor-critic methods

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 10774b93-9586-4dc5-adb2-f478da525fe6 · outbound

This paper cites Benchmarking Batch Deep Reinforcement Learning Algorithms.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Benchmarking Batch Deep Reinforcement Learning Algorithms

Reference 16

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Observation 7cfbce22-5b08-4573-b027-9c73c663fb99 · outbound

This paper cites Off-policy deep reinforcement learning without exploration.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Off-policy deep reinforcement learning without exploration

Reference 17

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Source-reported events for the cited work

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Observation 926af992-c702-4b00-9ccc-4afdc17cea4e · outbound

This paper cites Q-learning for robot control.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Q-learning for robot control

Reference 18

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Source-reported events for the cited work

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Observation 25c2fd69-746b-4dcc-91c0-a7000721a559 · outbound

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

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Why so pessimistic? estimating uncertainties for offline RL through ensembles, and why their independence matters

Reference 19

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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.

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Observation 9a57e88f-3bae-4844-8496-7a3b9c418607 · outbound

This paper cites Evaluating Reinforcement Learning Algorithms in Observational Health Settings.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Evaluating Reinforcement Learning Algorithms in Observational Health Settings

Reference 20

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Observation 253796a6-176b-407c-89ea-792783f1775f · outbound

This paper cites Learning pseudometric-based action representations for offline reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Learning pseudometric-based action representations for offline reinforcement learning

Reference 21

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Source-reported events for the cited work

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

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Observation 67773c32-af0b-416f-9d0e-170149a9d35e · outbound

This paper cites Efficient solution algorithms for factored MDPs.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Efficient solution algorithms for factored MDPs

Reference 22

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Observation cc55722f-4388-4a5e-ade7-b53c3857aaec · outbound

This paper cites Addressing extrapolation error in deep offline reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Addressing extrapolation error in deep offline reinforcement learning

Reference 23

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Observation 89c9d8f8-66ef-4572-9b9f-5106a487e404 · outbound

This paper cites Rl unplugged: A suite of benchmarks for offline reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Rl unplugged: A suite of benchmarks for offline reinforcement learning

Reference 24

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Observation 2a5989c3-19df-4335-b0a6-c03680d7a1ba · outbound

This paper cites Rainbow: Combining improvements in deep reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Rainbow: Combining improvements in deep reinforcement learning

Reference 25

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Observation 84a67943-1776-4f65-85bf-dfea4baa8eaf · outbound

This paper cites Distributed prioritized experience replay.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Distributed prioritized experience replay

Reference 26

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Observation df5e5766-7fac-464a-8fdc-d55a651b915f · outbound

This paper cites Learning and planning in complex action spaces.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Learning and planning in complex action spaces

Reference 27

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Source-reported events for the cited work

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Observation 9b3fe3ab-0316-4d50-a870-f038da66ad7c · outbound

This paper cites Revalued: Regularised ensemble value-decomposition for factorisable Markov decision processes.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Revalued: Regularised ensemble value-decomposition for factorisable Markov decision processes

Reference 28

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Observation 416971c4-2da5-42c9-8d1c-4eeb657dedc8 · outbound

This paper cites Planning with diffusion for flexible behavior synthesis.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Planning with diffusion for flexible behavior synthesis

Reference 29

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Source-reported events for the cited work

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Observation babaabdb-4031-4cda-bd8b-5b7356c91b11 · outbound

This paper cites Scalable deep reinforcement learning for vision-based robotic manipulation.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Scalable deep reinforcement learning for vision-based robotic manipulation

Reference 30

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Unavailable: canonical work link unavailable.

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Observation 21b95b16-5269-4173-9b8b-45194f4789f2 · outbound

This paper cites Efficient reinforcement learning in factored MDPs.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Efficient reinforcement learning in factored MDPs

Reference 31

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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 2026-08-23T06:30:58.430688+00:00.

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Observation 626988be-1b28-471c-a03d-b1f1d461101f · outbound

This paper cites MOReL : Model-based offline reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces MOReL : Model-based offline reinforcement learning

Reference 32

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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=2026-08-12T19:03:10.478100Z digest=sha256:5640aa324e2ca327df9b61a8c1fb167c49500f97b704442c1c772c820b72aaab

Observation 0a94f202-da42-486c-9de2-492ac413f4cb · outbound

This paper cites Adam: A Method for Stochastic Optimization.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Adam: A Method for Stochastic Optimization

Reference 33

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:03:10.481505Z digest=sha256:ad356b115a30db09eec2e221de1ee16b7b97e4a6f010708ad111c6274a8096ac

Observation e714f0af-3431-4f31-879c-41a872cae939 · outbound

This paper cites Al Sallab, Senthil Yogamani, and Patrick Pérez.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Al Sallab, Senthil Yogamani, and Patrick Pérez

Reference 34

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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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-12T19:03:10.484784Z digest=sha256:752093279deb711c8ff56b472d305d25e1e09e96dc8101785c913240884ba499

Observation 3d7a6251-7510-4dbd-9a5a-2f97013aa336 · outbound

This paper cites Offline reinforcement learning with Fisher divergence critic regularization.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Offline reinforcement learning with Fisher divergence critic regularization

Reference 35

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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=2026-08-12T19:03:10.488426Z digest=sha256:21313e60e29fb3baa0e98e74776df5279e141a6074941e73429bff2d471a4853

Observation 58fb6db3-dc3c-4ee4-b487-cf6267e6315b · outbound

This paper cites Offline reinforcement learning with implicit Q-Learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Offline reinforcement learning with implicit Q-Learning

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-12T19:03:11.113831Z

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=2026-08-12T19:03:10.492430Z digest=sha256:41570d1437fe525bafd82e93b55b3efa0bc1a2c0fd76f55bb87f3c2319913ad0

Observation e0c2110a-bfe4-4ff2-954f-31375e7c328e · outbound

This paper cites Multi-agent reinforcement learning as a rehearsal for decentralized planning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Multi-agent reinforcement learning as a rehearsal for decentralized planning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-12T19:03:10.496254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:03:10.496254Z digest=sha256:e2747b3a55609e76e77d023165410b88515b16a22f1aa63d8bf28c92e938afd5

Observation 0fe6e26c-5fe5-4392-a2a4-51790e31eb46 · outbound

This paper cites Stabilizing off-policy Q-learning via bootstrapping error reduction.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Stabilizing off-policy Q-learning via bootstrapping error reduction

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:11.092800Z

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=2026-08-12T19:03:10.499774Z digest=sha256:684cc244380b6ba0753a2a8a26d889b13bd417983b1b88980957416553165aa9

Observation 6397d9d5-6d8b-419d-be67-816ab20c37f7 · outbound

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

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Conservative Q-learning for offline reinforcement learning

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:11.081474Z

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=2026-08-12T19:03:10.503443Z digest=sha256:e012acb70e819e4098b61f60453a6d6ac611f84aacb6f9ec05a8befd31d2b618

Observation 482667be-589a-44a7-b1f0-a3a6ea0e5f05 · outbound

This paper cites Batch reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Batch reinforcement learning

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:11.067990Z

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=2026-08-12T19:03:10.507032Z digest=sha256:a3c3739f540d54a0592b9431f0da5847bf1f342532afca870c4de0cd839e58a4

Observation 92ab5873-4f1f-4cea-bb2f-3b4fcc7727e4 · outbound

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

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-12T19:03:10.510469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:03:10.510469Z digest=sha256:c0a7e5c75c21b93d9b3276b92f5011c1d496c4f2c48b91911dc1c1f800b53a77

Observation d0492a9d-cff5-476e-a5cf-41f08b30b80c · outbound

This paper cites Efficient large-scale fleet management via multi-agent deep reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Efficient large-scale fleet management via multi-agent deep reinforcement learning

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:11.053022Z

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=2026-08-12T19:03:10.514148Z digest=sha256:b48aaaa7cc37d3ee6f72b0a9de3312b859e7c46779511b0a7ff8508057960aab

Observation eaac4c8f-7871-4b17-9b51-0323444cf9f6 · outbound

This paper cites Reinforcement learning for clinical decision support in critical care: comprehensive review.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Reinforcement learning for clinical decision support in critical care: comprehensive review

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:11.041123Z

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=2026-08-12T19:03:10.517962Z digest=sha256:f1b908a460b99f1561d7e053bed7066c02f53995e2c5fdd1661838cd63640367

Observation aa51d450-5569-4890-887a-d9b9c2f8a8e7 · outbound

This paper cites Action-quantized offline reinforcement learning for robotic skill learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Action-quantized offline reinforcement learning for robotic skill learning

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:11.026124Z

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=2026-08-12T19:03:10.521881Z digest=sha256:6b8998fc520bdb2a2de8ec5022dc8d282a5c50a07edec912f83a4313198963b4

Observation 89284f3e-4c10-46e3-a682-0db39c9ca5de · outbound

This paper cites Benchmarking reinforcement learning algorithms on real-world robots.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Benchmarking reinforcement learning algorithms on real-world robots

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:11.011307Z

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=2026-08-12T19:03:10.525625Z digest=sha256:e1573c53dc18539a2f68061f0b5d017cb7a6b81350b775a2b6c6b5c7eac579bc

Observation cd53f65b-3894-4e0e-bb6b-debdafa96aad · outbound

This paper cites Discrete Sequential Prediction of Continuous Actions for Deep RL.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Discrete Sequential Prediction of Continuous Actions for Deep RL

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-12T19:03:10.529390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:03:10.529390Z digest=sha256:0de5bee03d83edb6cd832bca51be1e4e738e41173794bf861d7d8bc4277997b9

Observation 926ff78f-ebe2-4c76-89cf-6cd8f2e81b16 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Playing Atari with Deep Reinforcement Learning

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-12T19:03:10.533498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:03:10.533498Z digest=sha256:680c66f6f817befa394e19a3b27d50ef6e2757dd80855550d1592b7dc088a554

Observation 7b7926a9-c6e7-4acf-bb96-c22c647a7f43 · outbound

This paper cites Anti-exploration by random network distillation.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Anti-exploration by random network distillation

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-12T19:03:10.537601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:03:10.537601Z digest=sha256:ef7916671de0046c1aa2cacffda0344683016d30854a5b0b2f552d28840f805e

Observation da00f59f-5e12-470d-a0a4-8442804b6696 · outbound

This paper cites Factored action spaces in deep reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Factored action spaces in deep reinforcement learning

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.988698Z

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=2026-08-12T19:03:10.541576Z digest=sha256:21798553154e00228e1411bce96e2d76cecfa779acdb2b1864c0914244a314c8

Observation 6549ffa9-b9d2-4dc4-a43d-8dbf0ffc9911 · outbound

This paper cites Weighted qmix: Expanding monotonic value function factorisation for deep multi-agent reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Weighted qmix: Expanding monotonic value function factorisation for deep multi-agent reinforcement learning

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.976741Z

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=2026-08-12T19:03:10.545119Z digest=sha256:7d097da86fce84da7c9338b5d07c06721a77b4a7dde6163815ad5431ea242598

Observation e319e4c0-9e27-4c1e-9055-4699a7e52e34 · outbound

This paper cites Monotonic value function factorisation for deep multi-agent reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Monotonic value function factorisation for deep multi-agent reinforcement learning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.965680Z

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=2026-08-12T19:03:10.548563Z digest=sha256:56d7750dac310402bbed42dec481e56e1ae10b58e3c22c91fe4bb35ca1b5f25d

Observation de7082fb-8e4c-450c-9f41-e621efe6ba36 · outbound

This paper cites Leveraging factored action spaces for off-policy evaluation.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Leveraging factored action spaces for off-policy evaluation

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.953730Z

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=2026-08-12T19:03:10.552022Z digest=sha256:74939d99363eb3a13f9b45e9ae0a23ee40eab58adfa7ab2fa900f8524b29dce3

Observation 66922058-57ee-4157-86db-50125ea965e1 · outbound

This paper cites Is bang-bang control all you need? solving continuous control with Bernoulli policies.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Is bang-bang control all you need? solving continuous control with Bernoulli policies

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.942902Z

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=2026-08-12T19:03:10.555024Z digest=sha256:de156fd01492b5df8eff7e7054b06680ffbca93522dfce3181c50bd4741393fc

Observation d31d347b-2aa4-49e6-a28d-41688555a41d · outbound

This paper cites Solving continuous control via Q-learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Solving continuous control via Q-learning

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.930456Z

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=2026-08-12T19:03:10.557908Z digest=sha256:5826fcafeb1f9004ad956f4b9cfebbdd8660532d51c4693a8260363eebbbad29

Observation 6ad513da-4391-43df-bab6-67b1a63dfc25 · outbound

This paper cites Learning to Factor Policies and Action-Value Functions: Factored Action Space Representations for Deep Reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Learning to Factor Policies and Action-Value Functions: Factored Action Space Representations for Deep Reinforcement learning

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-12T19:03:10.694077Z

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=2026-08-12T19:03:10.560746Z digest=sha256:b1a62caec5997ccdf24f7d4ecdcb9807a7d4b8a32065629784f1936b2a2bb4ed

Observation 62c0ad27-6f49-4bfb-ab0a-8cace85207dd · outbound

This paper cites Value-Decomposition Networks For Cooperative Multi-Agent Learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Value-Decomposition Networks For Cooperative Multi-Agent Learning

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-12T19:03:10.563930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:03:10.563930Z digest=sha256:081a053eac76bca64b926573820ecf15b7f2ffa7ce6fcd269998c848f2bfbb8b

Observation da151567-1516-476d-86fe-e03a52b08055 · outbound

This paper cites Reinforcement learning: An introduction.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Reinforcement learning: An introduction

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-12T19:03:10.567010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:03:10.567010Z digest=sha256:b06c4c8c4befe8153c96bedfe7a0e95f02359f30dc235eba57a011a9dcc2c250

Observation b53450e0-fc4a-4d63-936e-84aac85b1e28 · outbound

This paper cites Overcoming model bias for robust offline deep reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Overcoming model bias for robust offline deep reinforcement learning

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.912011Z

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=2026-08-12T19:03:10.570496Z digest=sha256:7670428c22bea349812d243abcda4023d3cfa0264009aa3b26d4e59d8ae6fc68

Observation b0afe93c-5661-49a1-b6ec-7a8452097a63 · outbound

This paper cites Leveraging factored action spaces for efficient offline reinforcement learning in healthcare.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Leveraging factored action spaces for efficient offline reinforcement learning in healthcare

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.899804Z

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=2026-08-12T19:03:10.573946Z digest=sha256:0d2ced7c63a1383c95031eb50324bea98e32b03b1ab443fe4f60dc8df1bc4e7e

Observation 89cd17e2-af62-49dc-ab1f-6809f85b6990 · outbound

This paper cites Discretizing continuous action space for on-policy optimization.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Discretizing continuous action space for on-policy optimization

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.888097Z

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=2026-08-12T19:03:10.577735Z digest=sha256:d37b7293529c34c006443d5696c8764a99c07653c502f62e7dd8627868f09b76

Observation dc881ed4-c489-40ff-9e92-e1fe405df76d · outbound

This paper cites Action branching architectures for deep reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Action branching architectures for deep reinforcement learning

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-12T19:03:10.582027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:03:10.582027Z digest=sha256:98c7326091c6aa1fdd5bd51ba5b57e075246c10879c6c7eaad5dc8ccce07e623

Observation 15eb96b7-e6a9-444e-8428-a1231c7cf863 · outbound

This paper cites Issues in using function approximation for reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Issues in using function approximation for reinforcement learning

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.870116Z

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=2026-08-12T19:03:10.585574Z digest=sha256:dc42baade88ae1af1f30738353ae41bb6da809ffe413704d70869cf72c7df9f2

Observation 4e45167d-b1ad-4371-a45d-8154233ba893 · outbound

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

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces dm\_control: Software and tasks for continuous control

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-12T19:03:10.589045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:03:10.589045Z digest=sha256:b054d646d5d01572a75d5255f68d6dcec9653ac7fa8bec8c39ddfefbb39f35df

Observation 3c9fd57c-a71e-4ee5-9efe-fdc4934ec6dd · outbound

This paper cites Q-Learning in enormous action spaces via amortized approximate maximization.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Q-Learning in enormous action spaces via amortized approximate maximization

Reference 64

Resolution
verified exact
local_arxiv, observed 2026-08-12T19:03:10.668174Z

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=2026-08-12T19:03:10.592385Z digest=sha256:515a7a168a65f9f57cf251ede7511d6203dfdb69b63325335cd74291de8de0fb

Observation 48dd1f62-717e-45c1-bec5-08e23a57de46 · outbound

This paper cites Behavior Regularized Offline Reinforcement Learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Behavior Regularized Offline Reinforcement Learning

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-12T19:03:10.596540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:03:10.596540Z digest=sha256:d7605ef2eed6e1f6b1fedb914951b3f4512d48926e834fbc5ffc8dd81dc0f827

Observation bf18b59d-b88f-48ce-ada5-e298676a5bd3 · outbound

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

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces RORL : Robust offline reinforcement learning via conservative smoothing

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.852974Z

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=2026-08-12T19:03:10.600207Z digest=sha256:44d4ae62ac6c02fda9b37054865ec3284ca4f37b309d5961983f02d6846e3aff

Observation 7177f340-7afd-4c85-adfc-fbda40a250a6 · outbound

This paper cites Reinforcement learning in healthcare: A survey.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Reinforcement learning in healthcare: A survey

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.840494Z

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=2026-08-12T19:03:10.604130Z digest=sha256:683bf6aa8002c8fa18632cf0577bea57dcf204bb9abb221dc631bbcb6c6a47a8

Observation d5c1c604-2253-4a91-814f-4bba423b7656 · outbound

This paper cites MOPO : Model-based offline policy optimization.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces MOPO : Model-based offline policy optimization

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.828752Z

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=2026-08-12T19:03:10.608384Z digest=sha256:4a52d788d893d58aae623f0902d428973d39e5f9e0171fbcce991203495d771d

Observation 68c1c6c0-0f34-4fc2-94bc-e14ec62c22e0 · outbound

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

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces COMBO : Conservative offline model-based policy optimization

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.817118Z

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=2026-08-12T19:03:10.612100Z digest=sha256:1529a43ed7d98d0a78d09ca199979c882bc23248bb709695af0099cc4d1780e9

Observation 91331d7c-df83-4dd3-8aad-f7f0fa78d947 · outbound

This paper cites Deep reinforcement learning for page-wise recommendations.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces Deep reinforcement learning for page-wise recommendations

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.805460Z

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=2026-08-12T19:03:10.615617Z digest=sha256:704d4a82698b1e83a5a2d7827f0284320bf279a131c369e1574727e9474afdff

Observation ba122343-154d-4eb4-838e-b2460cc18d8e · outbound

This paper cites PLAS : Latent action space for offline reinforcement learning.

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces PLAS : Latent action space for offline reinforcement learning

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:03:10.793346Z

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=2026-08-12T19:03:10.619048Z digest=sha256:baf7d5b7a7ae372990e3d71fa74f26148c541ad9f1bcb1f80e2334bc72f42f63

Pith citing papers

No inbound Pith citation observations are available.