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Paper Citation Record · LEDGER

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer

As of 21 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2606.18959.

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

pith.paper-citation-record.v1
2606.18959 v1

Coverage vector

measured 35 of 35 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-06-26T21:03:44.697313Z

measured 35 of 35 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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  • verified fuzzy0
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Outbound references

Observation 2088d18a-9be2-494a-b891-d2e2e1d3ec66 · outbound

This paper cites Digit: A novel design for a low- cost compact high-resolution tactile sensor with application to in-hand manipulation,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Digit: A novel design for a low- cost compact high-resolution tactile sensor with application to in-hand manipulation,

Reference 1

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Observation 2268a4ad-e706-4892-8c53-672343ef6eb9 · outbound

This paper cites Gelsight: High-resolution robot tactile sensors for estimating geometry and force,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Gelsight: High-resolution robot tactile sensors for estimating geometry and force,

Reference 2

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Observation ab599298-cc8a-4baa-a515-f0c048a26595 · outbound

This paper cites Printed synaptic transistor–based electronic skin for robots to feel and learn,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Printed synaptic transistor–based electronic skin for robots to feel and learn,

Reference 3

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source=pdf_text observed=2026-06-26T21:03:44.697313Z digest=sha256:56c5733fbd7bc18660a45ac41cf8e7a2759dc0744b21a693cdf3c82037315503

Observation c0b0e80f-887b-4df5-a5f4-4bc882b06ab3 · outbound

This paper cites Artificial fingertip with embed- ded fiber-shaped sensing arrays for high resolution tactile sensing,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Artificial fingertip with embed- ded fiber-shaped sensing arrays for high resolution tactile sensing,

Reference 4

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source=pdf_text observed=2026-06-26T21:03:44.697313Z digest=sha256:589e8fa2669c94fe601b7df53dac6597baa495eea150e2a2ccb3c1b066d3d08a

Observation 7de26be6-31d0-406d-8eaa-1d44a3c27e58 · outbound

This paper cites Extended tactile perception: Vi- bration sensing through tools and grasped objects,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Extended tactile perception: Vi- bration sensing through tools and grasped objects,

Reference 5

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source=pdf_text observed=2026-06-26T21:03:44.697313Z digest=sha256:d85757bf5fe9d4708e83ed11b95752d2863da5f3aba5cbaa9871ee9f856141e2

Observation efae7a8d-dbfc-4b1d-a5f6-64088f40f279 · outbound

This paper cites Grip stabilization of novel objects using slip prediction,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Grip stabilization of novel objects using slip prediction,

Reference 6

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Observation 0812e6aa-accd-4e3e-90b6-af174646c10a · outbound

This paper cites Multimodal zero-shot learning for tactile texture recognition,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Multimodal zero-shot learning for tactile texture recognition,

Reference 7

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source=pdf_text observed=2026-06-26T21:03:44.697313Z digest=sha256:778c66a0c0976502e419a0331168a767d40135b8d78e9b6715d96e172d7005d4

Observation 097cb604-34ee-4981-8cb9-4407540fa2c1 · outbound

This paper cites Spatio-temporal attention model for tactile texture recognition,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Spatio-temporal attention model for tactile texture recognition,

Reference 8

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source=pdf_text observed=2026-06-26T21:03:44.697313Z digest=sha256:4070685808411535defe098de29dd746a353c72067b58db6cd6bce303bbd2b1f

Observation 389c68ef-51fb-4e3c-96e7-08c3f20c052c · outbound

This paper cites Tactile robotics: An outlook,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Tactile robotics: An outlook,

Reference 9

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source=pdf_text observed=2026-06-26T21:03:44.697313Z digest=sha256:92ff98df7d07041b840b123b91d2c628b37d9c02db04bccc8f31ea1474146abd

Observation b9124fc0-7014-4277-afca-40fce09fdec4 · outbound

This paper cites Anyrotate: Gravity-invariant in-hand object rotation with sim-to-real touch,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Anyrotate: Gravity-invariant in-hand object rotation with sim-to-real touch,

Reference 10

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source=pdf_text observed=2026-06-26T21:03:44.697313Z digest=sha256:8f50f41b584db1c4dc93b6fdd6596eff43cd58682347b406bb52e63653c97fad

Observation e32a0b81-2eff-4c33-9f58-81a37fe6c46b · outbound

This paper cites General in-hand object rotation with vision and touch,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer General in-hand object rotation with vision and touch,

Reference 11

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source=pdf_text observed=2026-06-26T21:03:44.697313Z digest=sha256:25dd1a22fd7573c871b0b60738199f77bb8d1d6f0c84360d61b7cf774592f57c

Observation 2c996cc5-cedf-4999-b74b-1d3853a9d453 · outbound

This paper cites Taxim: An example-based simulation model for gelsight tactile sensors,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Taxim: An example-based simulation model for gelsight tactile sensors,

Reference 12

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source=pdf_text observed=2026-06-26T21:03:44.697313Z digest=sha256:4ac354a0c3acd013d728a89ff6f8cbe6a7d9dcf002cd04ab6aa19ff0cde126ae

Observation c882b38b-bb97-4953-9a7d-f9ebac42be9b · outbound

This paper cites Fots: A fast optical tactile simulator for sim2real learning of tactile-motor robot manipulation skills,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Fots: A fast optical tactile simulator for sim2real learning of tactile-motor robot manipulation skills,

Reference 13

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source=pdf_text observed=2026-06-26T21:03:44.697313Z digest=sha256:811e10f1c6fdacee716535ff403c46d9da1d2e7f0d24512ac5cec2d9635d3189

Observation 8a9ddf58-c7d5-44ca-8883-b71ef98a295f · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Representation Learning with Contrastive Predictive Coding

Reference 14

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Observation 0bb995c5-4d68-4a5c-8c78-308c40c67534 · outbound

This paper cites Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning

Reference 15

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Observation c3677b05-b85a-4ff2-a26e-086c27cb07f2 · outbound

This paper cites Smith,ABAQUS/Standard User’s Manual, Version 6.9.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Smith,ABAQUS/Standard User’s Manual, Version 6.9

Reference 16

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Observation 2b75a2ed-bf9f-4a72-8254-d163f6be1fd1 · outbound

This paper cites Simulation of optical tactile sensors supporting slip and rotation using path tracing and impm,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Simulation of optical tactile sensors supporting slip and rotation using path tracing and impm,

Reference 17

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Observation 9e9a3383-2c74-415c-87c4-f297415e687f · outbound

This paper cites Tacsl: A library for visuotactile sensor simulation and learning,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Tacsl: A library for visuotactile sensor simulation and learning,

Reference 18

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Observation 6b777921-6927-4144-8a92-4fb6c22cdadf · outbound

This paper cites Taccel: Scaling up vision-based tactile robotics via high-performance GPU simulation,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Taccel: Scaling up vision-based tactile robotics via high-performance GPU simulation,

Reference 19

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Observation 030c3766-5b56-4d87-9ab2-06e2bad258a3 · outbound

This paper cites Univtac: A unified simulation platform for visuo-tactile manipulation data generation, learning, and benchmarking.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Univtac: A unified simulation platform for visuo-tactile manipulation data generation, learning, and benchmarking

Reference 20

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Observation 54cd62a0-b9b9-4350-870f-094a40450780 · outbound

This paper cites Elastic tactile simulation towards tactile- visual perception,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Elastic tactile simulation towards tactile- visual perception,

Reference 21

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Observation f06fd3b8-6721-46d3-8205-4d2760a2a37a · outbound

This paper cites Tactile sim-to-real policy transfer via real- to-sim image translation,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Tactile sim-to-real policy transfer via real- to-sim image translation,

Reference 22

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Observation cb5ffbe0-1f41-472c-9424-175143370c5d · outbound

This paper cites Tactgen: Tactile sensory data generation via zero-shot sim-to-real transfer,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Tactgen: Tactile sensory data generation via zero-shot sim-to-real transfer,

Reference 23

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Observation 9308cdb7-6e51-450b-865e-f4ed808010e1 · outbound

This paper cites Binding touch to everything: Learning unified multimodal tactile representations,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Binding touch to everything: Learning unified multimodal tactile representations,

Reference 24

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Observation 87154ad6-eab1-4fbf-b6fc-4069c85cb380 · outbound

This paper cites Multimodal visual-tactile rep- resentation learning through self-supervised contrastive pre-training,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Multimodal visual-tactile rep- resentation learning through self-supervised contrastive pre-training,

Reference 25

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Observation 650bc0de-ab8f-40cf-b7ca-f74f633f14ad · outbound

This paper cites Multi-modal representation learning with tactile data,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Multi-modal representation learning with tactile data,

Reference 26

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Observation 16a79c07-4f9d-4a29-879c-8505a7d7e872 · outbound

This paper cites Contrastive touch-to-touch pretraining,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Contrastive touch-to-touch pretraining,

Reference 27

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Observation 01b7cace-972f-49b5-843a-8764973c2943 · outbound

This paper cites Touch and go: Learning from human- collected vision and touch,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Touch and go: Learning from human- collected vision and touch,

Reference 28

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Observation 0d5e8901-7bd6-412e-ac91-f1c39f548646 · outbound

This paper cites M2curl: Sample-efficient multimodal reinforcement learning via self-supervised representation learning for robotic manipulation,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer M2curl: Sample-efficient multimodal reinforcement learning via self-supervised representation learning for robotic manipulation,

Reference 29

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Observation 83366690-cb9b-4f6b-92b9-4129ad8df052 · outbound

This paper cites Upvital: Unpaired visual-tactile self-supervised representation learning for dexterous robotic manipulation,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Upvital: Unpaired visual-tactile self-supervised representation learning for dexterous robotic manipulation,

Reference 30

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Observation 97c6961b-21bb-4a8a-a9b9-0b0b02e4f0d3 · outbound

This paper cites ViTacFormer: Learning Cross-Modal Representation for Visuo-Tactile Dexterous Manipulation.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer ViTacFormer: Learning Cross-Modal Representation for Visuo-Tactile Dexterous Manipulation

Reference 31

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Observation 81b4615e-4a48-48a6-8b8b-241028e9c0fa · outbound

This paper cites Sim-to-real for robotic tactile sensing via physics-based simulation and learned latent projections,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Sim-to-real for robotic tactile sensing via physics-based simulation and learned latent projections,

Reference 32

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Observation e5520ef2-ccb3-403d-b8b1-1233699a569d · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 33

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Observation ee73a1db-3752-4b38-afdd-e6b12c0d06b5 · outbound

This paper cites Efficient tactile simulation with differentiability for robotic manipulation,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Efficient tactile simulation with differentiability for robotic manipulation,

Reference 34

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Observation 81ad7780-3877-485e-9983-d55c65c72252 · outbound

This paper cites Visualizing data using t-sne,.

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer Visualizing data using t-sne,

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T21:03:44.697313Z digest=sha256:36e2f84a62ceff356a94215f8c02d1f521a8ec92a47b709b53cef3f2d7f7710d

Pith citing papers

No inbound Pith citation observations are available.