Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:14:15.972018Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 100 of 177 outbound references and 0 inbound Pith citation observations for arXiv:2507.09117.
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 2026-08-06T18:14:15.972018Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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
100 of 177 outbound references displayed
External citation measurements
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Observation 3e9deb41-8a88-4399-9cb3-32862f0478fd · outbound
Towards Human-level Dexterity via Robot Learning Ritter and R
Reference 1
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Observation 5659c2c2-d963-4534-a842-c35647797971 · outbound
Towards Human-level Dexterity via Robot Learning The coevolution of encephalization and manual dexterity in hominins and other primates,
Reference 2
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Observation 35af53e2-fcd5-433a-a63b-02fad6e97e96 · outbound
Towards Human-level Dexterity via Robot Learning Developmentofin-handmanipulationand relationship with activities,
Reference 3
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Observation a87209cc-263a-4c49-a5ab-f90a43601a31 · outbound
Towards Human-level Dexterity via Robot Learning How babies use their hands to learn about objects: Exploration, reach-to-grasp, manipulation, and tool use,
Reference 4
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Observation 5496e230-9bbd-4a17-a424-c7738f156748 · outbound
Towards Human-level Dexterity via Robot Learning Exploring hand dexterity in children with myelomeningocele,
Reference 5
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Observation 3cfbcd46-f229-465d-bf65-65cfa764c0ae · outbound
Towards Human-level Dexterity via Robot Learning The early motor milestones in infancy and later motor skills in toddlers: A structural equation model of motor development,
Reference 6
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Observation d3f4616a-58d2-456d-a05e-bc1d5fe18b14 · outbound
Towards Human-level Dexterity via Robot Learning Role of uncertainty in sensorimotor control,
Reference 7
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Observation 44fc161f-ee59-4810-8389-6a680f1877b9 · outbound
Towards Human-level Dexterity via Robot Learning A literature review of the universal and atomic elements of complex cognition,
Reference 8
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Observation 85fbd9bc-2069-4241-a8b6-e7baf0314bde · outbound
Towards Human-level Dexterity via Robot Learning DIGIT: A novel design for a low-cost compact high-resolution tactile sensor with application to in-hand manipulation,
Reference 9
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Observation 71402fd0-a93d-4f90-9218-aa3dbc5d07c3 · outbound
Towards Human-level Dexterity via Robot Learning Data-driventactilesensingusingspatiallyoverlappingsignals,
Reference 10
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Observation 262508e7-fe95-4298-99dc-18311b1469b8 · outbound
Towards Human-level Dexterity via Robot Learning GelSight: High-resolution robot tactile sensors for estimating geometry and force,
Reference 11
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Observation 3104e6b3-1724-4929-9f26-520a6e994195 · outbound
Towards Human-level Dexterity via Robot Learning Re-evaluation of the distribution of meissner’s corpuscles in human skin,
Reference 12
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Unavailable: canonical work link unavailable.
Observation 46840b3b-298a-469c-8491-88cf8d1b7ad2 · outbound
Towards Human-level Dexterity via Robot Learning Tactile dexterity: Manipulation primitives with tactile feedback,
Reference 13
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Observation 2d23c3d0-b8bc-4dfa-ab8c-3e5108dabcc7 · outbound
Towards Human-level Dexterity via Robot Learning Surveyoflearning-basedapproaches for robotic in-hand manipulation,
Reference 14
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Observation de85d2fa-bdd0-43df-8770-53da183340ce · outbound
Towards Human-level Dexterity via Robot Learning In-handmanipulationinyoungchildren: Rotation of an object in the fingers,
Reference 15
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Observation 4e082746-e078-4d98-941d-5f1580839c4a · outbound
Towards Human-level Dexterity via Robot Learning Solving rubik’s cube with a robot hand,
Reference 16
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Unavailable: canonical work link unavailable.
Observation 11c8c543-9f84-4f67-a67a-044749b10250 · outbound
Towards Human-level Dexterity via Robot Learning Dextrous tactile in-hand manipulation using a modular reinforcement learning architecture,
Reference 17
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Unavailable: canonical work link unavailable.
Observation 32227a29-7597-4b12-bfb2-7d0488df4735 · outbound
Towards Human-level Dexterity via Robot Learning Learning purely tactile in-hand manipulation with a torque-controlled hand,
Reference 18
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Observation 1f1635c9-9f19-40c6-aeef-6c59366a5460 · outbound
Towards Human-level Dexterity via Robot Learning AnyRotate: Gravity-invariant in-hand object rotation with sim-to-real touch,
Reference 19
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Observation b3478901-a4f7-4ec7-9f22-450a946b8c72 · outbound
Towards Human-level Dexterity via Robot Learning Transferring dexterous manipulation from GPU simulation to a remote real-world TriFinger,
Reference 20
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Unavailable: canonical work link unavailable.
Observation 5439db8c-888c-4152-8f87-c5455b711dd1 · outbound
Towards Human-level Dexterity via Robot Learning Visual dexterity: In-hand dexterous manipulation from depth,
Reference 21
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Observation 5534d186-9465-4698-a4ca-a363901da813 · outbound
Towards Human-level Dexterity via Robot Learning In-hand object rotation via rapid motor adaptation,
Reference 22
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Unavailable: canonical work link unavailable.
Observation 2994c133-e7d3-449b-827e-c0b5a82deff6 · outbound
Towards Human-level Dexterity via Robot Learning On the feasibility of learning finger- gaiting in-hand manipulation with intrinsic sensing,
Reference 23
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Unavailable: canonical work link unavailable.
Observation 560ec3a9-27a5-44e4-ae2d-e893c1a31f82 · outbound
Towards Human-level Dexterity via Robot Learning Sampling- based exploration for reinforcement learning of dexterous manipulation,
Reference 24
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Unavailable: canonical work link unavailable.
Observation 01244160-ea98-4d57-835c-8ee59ce57c14 · outbound
Towards Human-level Dexterity via Robot Learning General in-hand object rotation with vision and touch,
Reference 25
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Unavailable: canonical work link unavailable.
Observation 3b7a9c89-8ba4-4856-aaaf-534285f5de44 · outbound
Towards Human-level Dexterity via Robot Learning Rotating without seeing: Towards in-handdexteritythroughtouch,
Reference 26
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Observation fee012f5-c497-4e0c-808d-63e70301bf2a · outbound
Towards Human-level Dexterity via Robot Learning Dextroustactilein-handmanipulationusinga modular reinforcement learning architecture,
Reference 27
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Observation 924c9975-5fa0-44c0-bcc2-326de37979d0 · outbound
Towards Human-level Dexterity via Robot Learning Tactile sensing for dexterous in-hand manip- ulation in robotics—a review,
Reference 28
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Observation 46d4850d-fa13-49ef-899a-c67e5d90f62d · outbound
Towards Human-level Dexterity via Robot Learning Tactile sensors for friction estimation and incipient slip detection—toward dexterous robotic manipulation: A review,
Reference 29
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Unavailable: canonical work link unavailable.
Observation 7a53fba5-f231-46d1-a685-ee3921fe4807 · outbound
Towards Human-level Dexterity via Robot Learning TEXterity – tactile extrinsic deXterity: Simultaneous tactile estimation and control for extrinsic dexterity,
Reference 30
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Observation 9f0017d7-5183-45e2-ac70-cb7f4442e8c6 · outbound
Towards Human-level Dexterity via Robot Learning Generalizedexplorationinpolicysearch,
Reference 31
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Observation 52204cf3-1e80-418b-b3b6-b66496df8c93 · outbound
Towards Human-level Dexterity via Robot Learning Towards learning to play piano with dexterous hands and touch,
Reference 32
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Observation e805246b-2c9d-44cc-8439-85d408d00811 · outbound
Towards Human-level Dexterity via Robot Learning Neural feels with neural fields: Visuo-tactile perception for in-hand manipulation,
Reference 33
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Observation 5b64749e-f6e1-4856-8690-9645745c4667 · outbound
Towards Human-level Dexterity via Robot Learning Thefutureliesinapairoftactilehands,
Reference 34
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Observation e24cd538-f066-4f2c-8b94-5d5a2bf5632c · outbound
Towards Human-level Dexterity via Robot Learning DexiTac: Soft dexterous tactile gripping,
Reference 35
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Observation 7ffd6d2e-5514-4bf9-ae1b-be2d16224484 · outbound
Towards Human-level Dexterity via Robot Learning Lessons from learning to spin “pens
Reference 36
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Observation aa9426f4-70bf-4cc1-9b05-33de7750c760 · outbound
Towards Human-level Dexterity via Robot Learning Diffusion policy: Visuomotor policy learning via action diffusion,
Reference 37
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Observation 4be91216-bc8c-4061-82a9-273996528077 · outbound
Towards Human-level Dexterity via Robot Learning Learningfine-grainedbimanualmanipulation with low-cost hardware,
Reference 38
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Observation 5c3469e6-8f67-4f32-98f0-085e4311bd76 · outbound
Towards Human-level Dexterity via Robot Learning Waypoint-based imitation learning for robotic manipulation,
Reference 39
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Observation de3537c8-6459-46c6-ad2d-c302df05a699 · outbound
Towards Human-level Dexterity via Robot Learning Learningfine-grainedbimanualmanipulation with low-cost hardware,
Reference 40
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Observation 501f7025-ddfc-43a7-be92-7efeac1f50b9 · outbound
Towards Human-level Dexterity via Robot Learning Diffusion policy: Visuomotor policy learning via action diffusion,
Reference 41
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Unavailable: canonical work link unavailable.
Observation 448f1bc7-a474-4fcb-b803-184a2d2ff2bc · outbound
Towards Human-level Dexterity via Robot Learning RoboAgent: Generalizationandefficiencyinrobotmanipulationviasemanticaugmentationsandaction chunking,
Reference 42
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Observation ffe7a400-4bc4-4c55-a9d3-8117f9e9df1a · outbound
Towards Human-level Dexterity via Robot Learning Learningtograsptheungraspablewithemergentextrinsicdexterity,
Reference 43
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Observation 786c184b-1353-45ef-89d7-283e5a8c0b17 · outbound
Towards Human-level Dexterity via Robot Learning Extremeparkourwithleggedrobots,
Reference 44
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Observation ab17e04d-fd7f-490f-b0cd-fe3fe0789a0b · outbound
Towards Human-level Dexterity via Robot Learning Learning quadrupedal locomotion over challenging terrain,
Reference 45
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Observation 6159c6dd-c067-49dc-a5eb-4b520b7f319d · outbound
Towards Human-level Dexterity via Robot Learning Learning agile and dynamic motor skills for legged robots,
Reference 46
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Observation 213b0412-9f2c-42ff-9236-2537e6a89843 · outbound
Towards Human-level Dexterity via Robot Learning Robot parkour learning,
Reference 47
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Observation 4a4ee126-8ed8-43e9-9764-5a07256bb600 · outbound
Towards Human-level Dexterity via Robot Learning BC-Z:Zero-shottaskgeneralizationwithroboticimitationlearning,
Reference 48
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Observation 11cde259-0dab-476c-abc2-02a302485b77 · outbound
Towards Human-level Dexterity via Robot Learning RT-1:Roboticstransformerforreal-worldcontrolatscale,
Reference 49
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Observation bf696224-221d-476d-b022-160a169912d0 · outbound
Towards Human-level Dexterity via Robot Learning RoboCat: A self-improving foundation agent for robotic manipula- tion,
Reference 50
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Observation 7cf74968-7c93-4f9c-a061-54410eb6ab99 · outbound
Towards Human-level Dexterity via Robot Learning RT-2:Vision-language-actionmodelstransferwebknowledgetorobotic control,
Reference 51
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Observation 53c177d8-7123-4476-b5ad-383c251a93a6 · outbound
Towards Human-level Dexterity via Robot Learning Domainrandomization for transferring deep neural networks from simulation to the real world,
Reference 52
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Observation 54afc476-ee91-43fc-9092-fa63a0fb327a · outbound
Towards Human-level Dexterity via Robot Learning Online vs. offline adaptive domain randomization benchmark,
Reference 53
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Observation 119d65fb-44be-4879-bf50-902045e1d1e7 · outbound
Towards Human-level Dexterity via Robot Learning RMA: Rapid motor adaptation for legged robots,
Reference 54
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Observation 178262fe-4836-4da5-99b8-8d08b38fffc8 · outbound
Towards Human-level Dexterity via Robot Learning Reconcilingrealitythroughsimulation:Areal-to-sim-to-realapproachfor robust manipulation,
Reference 55
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Observation 6cf73f85-645c-4839-8a9c-4da7e6dcb005 · outbound
Towards Human-level Dexterity via Robot Learning Anoverviewofdexterousmanipulation,
Reference 56
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Observation d7960918-b044-4880-b338-f67b377eb895 · outbound
Towards Human-level Dexterity via Robot Learning On dexterity and dexterous manipulation,
Reference 57
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Observation 0cf72879-43b0-4d2e-8f42-efb040ae0027 · outbound
Towards Human-level Dexterity via Robot Learning Reorientingobjectswitharobothandusinggraspgaits,
Reference 58
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Observation e64dcea3-2e3b-43ff-be82-117fa46e2527 · outbound
Towards Human-level Dexterity via Robot Learning Dextrous manipulation by rolling and finger gaiting,
Reference 59
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Observation 014a371d-3087-4565-bea3-30bd45dd26f3 · outbound
Towards Human-level Dexterity via Robot Learning Manipulation gaits: Sequences of grasp control tasks,
Reference 60
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Observation c19fdb92-cb67-465b-9e34-33c682d43770 · outbound
Towards Human-level Dexterity via Robot Learning Dexterous manipulation planning using probabilistic roadmaps in continuous grasp subspaces,
Reference 61
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Observation 12f6eb5e-7d28-47fe-a98c-6c00a4fd9b8c · outbound
Towards Human-level Dexterity via Robot Learning Regrasps by a multifingered hand based on primitives,
Reference 62
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Observation 8d0773c0-4ab5-4cec-bcb2-25edf0ed7cc1 · outbound
Towards Human-level Dexterity via Robot Learning Chapter 8 markov decision processes,
Reference 63
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Observation a029af11-c92c-4750-bd9f-5de755d16ffc · outbound
Towards Human-level Dexterity via Robot Learning MuJoCo: A physics engine for model-based control,
Reference 64
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Observation 9f7c30dc-9fb2-4141-a715-01260c81da3a · outbound
Towards Human-level Dexterity via Robot Learning Synthesisandstabilizationofcomplexbehaviorsthrough online trajectory optimization,
Reference 65
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Observation bd4384e7-c73e-4951-a56b-d5a8104dc946 · outbound
Towards Human-level Dexterity via Robot Learning Discoveryofcomplexbehaviorsthroughcontact- invariant optimization,
Reference 66
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Observation d35df40d-fa99-41e2-a0b0-51b6cc8454fd · outbound
Towards Human-level Dexterity via Robot Learning Real-time robust finger gaits planning under object shape and dynamics uncertainties,
Reference 67
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Observation 8714ad86-2e85-4226-8836-5a11d1ce4f8d · outbound
Towards Human-level Dexterity via Robot Learning Geometric in-hand regrasp planning: Alternating optimization of finger gaits and in-grasp manipulation,
Reference 68
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Observation 7e58bd66-b83e-4c65-a7ec-349b14ecca76 · outbound
Towards Human-level Dexterity via Robot Learning Solvingchallengingdexterousmanipulationtaskswith trajectory optimisation and reinforcement learning,
Reference 69
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Observation d61adb8f-d9e6-4e2b-98c4-08f8a9f42216 · outbound
Towards Human-level Dexterity via Robot Learning Complementarity-free multi-contact modeling and optimization for dexterous manipulation,
Reference 70
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Observation b4c96a0f-824b-42aa-b946-203ca78f81fa · outbound
Towards Human-level Dexterity via Robot Learning Randomized manipulation planning for a multi-fingered hand by switching contact modes,
Reference 71
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Observation 17d7533f-afbd-4099-af8e-f4ba94452ce3 · outbound
Towards Human-level Dexterity via Robot Learning Finger gaits planning for multifingered manipulation,
Reference 72
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Observation 8f718a8a-4bb6-4885-ac0f-bc0bc9dd48e0 · outbound
Towards Human-level Dexterity via Robot Learning Learning dexterous in-hand manipulation,
Reference 73
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Observation 893a6248-2ab9-45f6-b44b-7c309015d2bb · outbound
Towards Human-level Dexterity via Robot Learning Learning complex dexterous manipulation with deep reinforcement learning and demonstrations,
Reference 74
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Observation 62f35eb4-54a1-4325-b4d0-918f29497695 · outbound
Towards Human-level Dexterity via Robot Learning Dexterousmanipulationwithdeepreinforcement learning: Efficient, general, and low-cost,
Reference 75
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Observation 74288157-f039-4e81-a3f1-d37ec08d256b · outbound
Towards Human-level Dexterity via Robot Learning State-only imitation learning for dexter- ous manipulation,
Reference 76
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Observation c2941ece-32c0-4792-a8a5-c7f3986be241 · outbound
Towards Human-level Dexterity via Robot Learning Generalizationindexterousmanipulation via geometry-aware multi-task learning,
Reference 77
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Observation 0ff11a24-9e19-4500-b798-b52f909b3110 · outbound
Towards Human-level Dexterity via Robot Learning Isaac gym: High performance GPU-based physics simulation for robot learning,
Reference 78
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Observation 16a556d3-3b19-4f46-9fad-4c300c047461 · outbound
Towards Human-level Dexterity via Robot Learning DeXtreme: Transfer of agile in-hand manipulation from simulation to reality,
Reference 79
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Observation 24081219-c422-4224-9cfa-5b30d3695e38 · outbound
Towards Human-level Dexterity via Robot Learning Precision object manipulation with a multifingered robot hand,
Reference 80
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Observation 7e5a13df-2fac-4580-84f2-b719ea826022 · outbound
Towards Human-level Dexterity via Robot Learning Learningrobotin-handmanipulation with tactile features,
Reference 81
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Observation a102ca8f-98af-4913-9f3c-a3d461eb32da · outbound
Reference 82
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Observation 3553adc8-2e78-400b-a609-eb74c2dbd805 · outbound
Towards Human-level Dexterity via Robot Learning Using tactile sensing to improve the sample efficiency and performance of deep deterministic policy gradients for simulated in-hand manipulation tasks,
Reference 83
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Observation 035afecf-4967-459d-92bb-479e4b81d01c · outbound
Towards Human-level Dexterity via Robot Learning Deepdynamicsmodelsforlearningdexterous manipulation,
Reference 84
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Observation 6cc003de-86ab-43ed-96a3-2c7d03f8e28a · outbound
Towards Human-level Dexterity via Robot Learning Modelpredictiveactor-critic:Acceleratingrobotskillacquisitionwithdeepreinforcement learning,
Reference 85
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Observation 8b5d9574-0bc7-4cd2-ab89-e1651454c9bb · outbound
Towards Human-level Dexterity via Robot Learning Surprisinglyrobustin-handmanipulation: An empirical study,
Reference 86
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Observation 13783dee-1cde-4a16-8a08-51e245bdc967 · outbound
Towards Human-level Dexterity via Robot Learning Onthefeasibilityoflearningfinger-gaiting in-hand manipulation with intrinsic sensing,
Reference 87
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Observation 1ff6e1b9-c868-4e67-801c-4fc33f5814c5 · outbound
Towards Human-level Dexterity via Robot Learning A system for general in-hand object re-orientation,
Reference 88
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Observation fcded2c4-4bc7-46df-abf9-5f9894e593b1 · outbound
Towards Human-level Dexterity via Robot Learning Estimator-coupled reinforcement learning for robust purely tactile in-hand manipulation,
Reference 89
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Observation 022de441-173b-4b26-af3a-ecb050e21897 · outbound
Towards Human-level Dexterity via Robot Learning Rotating without seeing: Towards in-hand dexterity through touch,
Reference 90
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Observation 5228a85f-0d54-4cd6-b60d-85b09bfbfa1d · outbound
Towards Human-level Dexterity via Robot Learning Robot synesthesia: In-hand manipulation with visuotactile sensing,
Reference 91
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Observation 073ea48b-bfe5-4df3-aab4-78f526498f38 · outbound
Towards Human-level Dexterity via Robot Learning General In-Hand Object Rotation with Vision and Touch
Reference 92
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Observation 79ec4743-e621-4a4e-a43a-31dd05c88698 · outbound
Towards Human-level Dexterity via Robot Learning Sampling-based exploration for reinforcement learning of dexterous manipulation,
Reference 93
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Observation 9f3a68bd-88a7-4157-8af1-4ed59f49af86 · outbound
Towards Human-level Dexterity via Robot Learning Hierarchical tactile-based control decomposition of dexterous in-hand manipulation tasks,
Reference 94
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Observation 611eeab9-1acd-4982-bb18-bf05197094d6 · outbound
Towards Human-level Dexterity via Robot Learning Learninghierarchicalcontrol for robust in-hand manipulation,
Reference 95
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Observation 9dbe4487-2f00-4e40-a71b-9704e09a6cff · outbound
Towards Human-level Dexterity via Robot Learning AC-teach: A bayesianactor-criticmethodforpolicylearningwithanensembleofsuboptimalteachers,
Reference 96
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Observation 47149bc0-edbb-47c3-a104-0b3350827a4b · outbound
Towards Human-level Dexterity via Robot Learning Learningdexterousmanipulationfromsuboptimalexperts,
Reference 97
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Observation d0590e25-c863-4a71-adfe-fb2a222e8db1 · outbound
Towards Human-level Dexterity via Robot Learning Zhang, PEX: Policy expansion for bridging offline-to-online reinforcement learning (ICLR23)
Reference 98
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Observation a4a7ea2d-b670-4627-a05b-48755a1a02cf · outbound
Towards Human-level Dexterity via Robot Learning R ×R:RapideXplorationforreinforcementlearningviasampling-based reset distributions and imitation pre-training,
Reference 99
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Observation fabd89dd-b466-42d9-9836-af853f09ca35 · outbound
Towards Human-level Dexterity via Robot Learning Curiosity-driven exploration by self- supervised prediction,
Reference 100
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No inbound Pith citation observations are available.