Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T04:21:20.555798Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2608.06544.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T04:21:20.555798Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
51 of 51 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 5ca07c5f-125d-44aa-994e-1c41f8f5d831 · outbound
TaskSense: Focusing on What Matters in World Models Categorical Reparameterization with Gumbel-Softmax
Reference 1
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Observation 109f9c5b-83f5-4468-afb4-f4b8b53c37ba · outbound
TaskSense: Focusing on What Matters in World Models Dream to Control: Learning Behaviors by Latent Imagination
Reference 2
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Observation d4438d72-2036-409f-acc6-1044dec366cb · outbound
TaskSense: Focusing on What Matters in World Models Advances in Neural Information Processing Systems , volume=
Reference 3
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Observation 4f567f88-4c73-4ec4-b4e8-268c50d6b30c · outbound
TaskSense: Focusing on What Matters in World Models CURL: Contrastive Unsupervised Representations for Reinforcement Learning
Reference 4
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Observation e1f9b8a2-ccfa-4a61-b905-32c52e645684 · outbound
TaskSense: Focusing on What Matters in World Models Temporal Difference Learning for Model Predictive Control
Reference 5
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Observation 9c124f22-d6b5-48c4-9457-f77b361c0210 · outbound
TaskSense: Focusing on What Matters in World Models Nature , volume=
Reference 6
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Observation 598dd703-9069-434e-a509-d80dca1144a7 · outbound
TaskSense: Focusing on What Matters in World Models Learning Invariant Representations for Reinforcement Learning without Reconstruction
Reference 7
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Observation 644d7c9e-273d-4df7-a7ff-adbdc3bf6f5b · outbound
TaskSense: Focusing on What Matters in World Models Mastering Atari with Discrete World Models
Reference 8
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Observation 5592443c-77c2-47b9-a5b0-786961428b32 · outbound
TaskSense: Focusing on What Matters in World Models Transformers are Sample-Efficient World Models
Reference 9
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Observation d3cc9338-6b1e-4ab0-a1a0-fb419b7eb491 · outbound
TaskSense: Focusing on What Matters in World Models Advances in Neural Information Processing Systems , volume=
Reference 10
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Observation 44b85895-3308-4054-8c74-616ef4239792 · outbound
TaskSense: Focusing on What Matters in World Models Proceedings of SSST-8, eighth workshop on syntax, semantics and structure in statistical translation , pages=
Reference 11
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Observation 0d6c1a78-86ae-4a95-8a93-10b35753fcd3 · outbound
TaskSense: Focusing on What Matters in World Models nature , volume=
Reference 12
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Observation 71f9e664-e9f6-4391-b622-a4a6f73fcb42 · outbound
TaskSense: Focusing on What Matters in World Models Proceedings of the aaai conference on artificial intelligence , volume=
Reference 13
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Observation 74f8d01f-455b-4371-8215-dac9f2fd2a72 · outbound
TaskSense: Focusing on What Matters in World Models The 2017 DAVIS Challenge on Video Object Segmentation , journal =
Reference 14
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Observation 48aecb7b-58ad-4fdc-bbbc-60259c62b69d · outbound
TaskSense: Focusing on What Matters in World Models Proceedings of the IEEE international conference on computer vision , pages=
Reference 15
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Observation 821add74-a10f-4c3f-9f09-43bb97ca7422 · outbound
TaskSense: Focusing on What Matters in World Models International Conference on Machine Learning , pages=
Reference 16
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Observation fa6bd076-424b-454b-bd84-89e4193e9761 · outbound
TaskSense: Focusing on What Matters in World Models Advances in neural information processing systems , year=
Reference 17
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Observation 9edada14-d3d7-490d-8927-13f5907a655e · outbound
TaskSense: Focusing on What Matters in World Models D4RL: Datasets for Deep Data-Driven Reinforcement Learning
Reference 18
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Observation c5490981-e197-497a-b9c3-9ff994b3c9c2 · outbound
TaskSense: Focusing on What Matters in World Models Rethinking Full Connectivity in Recurrent Neural Networks
Reference 19
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Observation dc88a8ba-8550-44f3-a10b-da2d551ccf70 · outbound
TaskSense: Focusing on What Matters in World Models Provable RL with Exogenous Distractors via Multistep Inverse Dynamics
Reference 20
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Observation 86b95898-84a5-4e93-85f3-27aa093e14c0 · outbound
TaskSense: Focusing on What Matters in World Models Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models
Reference 21
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Observation f4cbfe08-29f9-4a48-8c04-80773dba5ccb · outbound
TaskSense: Focusing on What Matters in World Models International conference on learning representations , year=
Reference 22
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Observation ff768f15-bfbc-4b68-9728-0f86ef9e8d6c · outbound
TaskSense: Focusing on What Matters in World Models Conference on Robot Learning , pages=
Reference 23
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Observation 99274f1f-7d1a-47a1-bea6-8717f1fc9784 · outbound
TaskSense: Focusing on What Matters in World Models Loss is its own Reward: Self-Supervision for Reinforcement Learning
Reference 24
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Observation 2d9b85d0-3e51-4c48-9d16-02081fd36bad · outbound
TaskSense: Focusing on What Matters in World Models International conference on machine learning , pages=
Reference 25
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Observation 67c5a02d-dcd8-4854-80ed-3554f85f1854 · outbound
TaskSense: Focusing on What Matters in World Models Advances in neural information processing systems , volume=
Reference 26
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Observation f69beb38-5e57-4822-8c54-577c36017f64 · outbound
TaskSense: Focusing on What Matters in World Models Learning Latent Dynamic Robust Representations for World Models
Reference 27
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Observation cfb177bf-f275-4f4f-8db3-77fe1a201616 · outbound
TaskSense: Focusing on What Matters in World Models SOLD: Slot Object-Centric Latent Dynamics Models for Relational Manipulation Learning from Pixels
Reference 28
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Observation 40566d2a-0a4d-41e1-9c1a-19397f94ea9f · outbound
TaskSense: Focusing on What Matters in World Models ACM Sigart Bulletin , volume=
Reference 29
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Observation 3f214913-4e11-4365-b992-8c178d4a3865 · outbound
TaskSense: Focusing on What Matters in World Models World Models
Reference 30
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Observation 61c8dca5-f514-4456-8160-256e7957d7ca · outbound
TaskSense: Focusing on What Matters in World Models Mastering Diverse Domains through World Models
Reference 31
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Observation 8a3be207-cc0e-4760-9810-3dcbbd26c621 · outbound
TaskSense: Focusing on What Matters in World Models International conference on machine learning , pages=
Reference 32
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Observation 5ebca4ec-ff3a-463b-aeea-a0187a746460 · outbound
TaskSense: Focusing on What Matters in World Models Learning Transformer-based World Models with Contrastive Predictive Coding
Reference 33
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Observation ebd258ec-d475-4b95-b9b0-5e014e075930 · outbound
TaskSense: Focusing on What Matters in World Models Nature , volume=
Reference 34
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Observation 0313ff84-bba8-4561-864f-ffd2c45bd2c2 · outbound
TaskSense: Focusing on What Matters in World Models The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
Reference 35
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Observation dc378637-ab26-4252-8f84-6bea917e9480 · outbound
TaskSense: Focusing on What Matters in World Models DeepMind Control Suite
Reference 36
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Observation a0ae7e1b-a464-413e-a0be-0d6ab998ab83 · outbound
TaskSense: Focusing on What Matters in World Models Journal of artificial intelligence research , volume=
Reference 37
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Observation d8571a63-3d3d-4c08-81bd-a7ac0fbc4203 · outbound
TaskSense: Focusing on What Matters in World Models The Distracting Control Suite -- A Challenging Benchmark for Reinforcement Learning from Pixels
Reference 38
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Observation 21f032bb-8ccd-4f04-80a2-27075ba65db0 · outbound
TaskSense: Focusing on What Matters in World Models arXiv preprint arXiv:2603.18202 , year=
Reference 39
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Observation 6fb209f9-baca-4c89-83f8-472aab110e24 · outbound
TaskSense: Focusing on What Matters in World Models International conference on machine learning , pages=
Reference 40
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Observation 2b5e63f2-cb1c-4b51-849a-46371eb53c60 · outbound
TaskSense: Focusing on What Matters in World Models Communication, Simulation, and Intelligent Agents: Implications of Personal Intelligent Machines for Medical Education
Reference 41
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Observation f627ff9b-fcb6-448e-b983-09b401a1ad24 · outbound
TaskSense: Focusing on What Matters in World Models Classification Problem Solving
Reference 42
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Observation 893b7363-c003-4230-8de7-179a6c5dff0a · outbound
TaskSense: Focusing on What Matters in World Models , title =
Reference 43
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Observation cd53a1b3-bd7e-401c-b13d-94fcc189edeb · outbound
TaskSense: Focusing on What Matters in World Models New Ways to Make Microcircuits Smaller---Duplicate Entry
Reference 44
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Observation ef874fd1-aeda-42d7-9a67-e93872ac6865 · outbound
TaskSense: Focusing on What Matters in World Models Clancey and Glenn Rennels , abstract =
Reference 45
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Observation 02a4b242-2747-4fd8-bf96-33dd7dc718f7 · outbound
TaskSense: Focusing on What Matters in World Models and Rennels, Glenn R
Reference 46
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Observation 1e7013f6-d6c9-483e-9aab-e2f36636b303 · outbound
TaskSense: Focusing on What Matters in World Models Poligon: A System for Parallel Problem Solving
Reference 47
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Observation 4c5df7b1-8136-4d7a-b3f6-4574f4fe37cd · outbound
TaskSense: Focusing on What Matters in World Models Transfer of Rule-Based Expertise through a Tutorial Dialogue
Reference 48
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Observation fb3dd647-68d9-41a5-b9f1-94ffab984711 · outbound
TaskSense: Focusing on What Matters in World Models The Engineering of Qualitative Models
Reference 49
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Observation 869cd5e3-d60c-4542-b9e9-af8071305bcf · outbound
TaskSense: Focusing on What Matters in World Models 2023 , eprint=
Reference 50
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Observation f69548f0-eccb-4675-bc04-027eef1911dc · outbound
TaskSense: Focusing on What Matters in World Models Pluto: The 'Other' Red Planet
Reference 51
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No inbound Pith citation observations are available.