Paper Citation Record · LEDGER

Self-Supervised Visuo-Tactile Pretraining to Locate and Follow Garment Features

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2209.13042.

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

pith.paper-citation-record.v1
2209.13042 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:47:43.020932Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T15:37:05.793312Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5ed7388f-1502-4e34-a916-254c4ab1ec05 · inbound

ConViTac: Aligning Visual-Tactile Fusion with Contrastive Representations cites this paper.

ConViTac: Aligning Visual-Tactile Fusion with Contrastive Representations Self-Supervised Visuo-Tactile Pretraining to Locate and Follow Garment Features

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T22:47:43.020932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c070a829-0b83-4839-9333-f6a0329afe63 · inbound

Seeing Through Touch: Tactile-Driven Visual Localization of Material Regions cites this paper.

Seeing Through Touch: Tactile-Driven Visual Localization of Material Regions Self-Supervised Visuo-Tactile Pretraining to Locate and Follow Garment Features

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:41:04.489523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 76f25e6c-b7a8-42c5-aeab-2a6250d13850 · inbound

Heterogeneous Tactile Transformer cites this paper.

Heterogeneous Tactile Transformer Self-Supervised Visuo-Tactile Pretraining to Locate and Follow Garment Features

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-06-30T05:54:18.375061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a5145366-09a0-4d3d-8942-630e2ee6f84e · inbound

UniTac: A Unified Multimodal Model for Cross-Sensor Tactile Understanding and Generation cites this paper.

UniTac: A Unified Multimodal Model for Cross-Sensor Tactile Understanding and Generation Self-Supervised Visuo-Tactile Pretraining to Locate and Follow Garment Features

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T10:05:40.685930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 37f76a58-528f-410a-ad1a-43d781a8a5c4 · inbound

Wake up for Touch! Mask-isolated Tactile Alignment Learning in MLLMs cites this paper.

Wake up for Touch! Mask-isolated Tactile Alignment Learning in MLLMs Self-Supervised Visuo-Tactile Pretraining to Locate and Follow Garment Features

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T15:37:05.795098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 28119619-0b4b-4581-901b-b61c11f2e116 · inbound

{\tau}: Learning Touch-Augmented Vision-Language-Action Models from Future Visual Supervision cites this paper.

{\tau}: Learning Touch-Augmented Vision-Language-Action Models from Future Visual Supervision Self-Supervised Visuo-Tactile Pretraining to Locate and Follow Garment Features

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-31T13:36:04.083852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.