Paper Citation Record · LEDGER

Quantitative Survey of the State of the Art in Sign Language Recognition

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2008.09918.

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

pith.paper-citation-record.v1
2008.09918 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:16:00.449596Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T04:55:23.623045Z

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 b0fedbe0-a361-4b67-9984-de6c112eb45c · inbound

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation cites this paper.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Quantitative Survey of the State of the Art in Sign Language Recognition

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T13:16:00.449596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 645d55b1-6f29-4843-b478-22a0c0826c13 · inbound

Sign-IDD: Iconicity Disentangled Diffusion for Sign Language Production cites this paper.

Sign-IDD: Iconicity Disentangled Diffusion for Sign Language Production Quantitative Survey of the State of the Art in Sign Language Recognition

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T13:01:56.128412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35b789cd-d4bb-4d33-b693-c277b97c3f07 · inbound

StgcDiff: Spatial-Temporal Graph Condition Diffusion for Sign Language Transition Generation cites this paper.

StgcDiff: Spatial-Temporal Graph Condition Diffusion for Sign Language Transition Generation Quantitative Survey of the State of the Art in Sign Language Recognition

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T00:41:18.529061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3428d75-cb53-458a-aacb-7725b5feb8c3 · inbound

Bringing Balance to Hand Shape Classification: Mitigating Data Imbalance Through Generative Models cites this paper.

Bringing Balance to Hand Shape Classification: Mitigating Data Imbalance Through Generative Models Quantitative Survey of the State of the Art in Sign Language Recognition

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T15:03:48.611672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 727599fd-dca4-41f8-a2db-3d8f88c3a004 · inbound

The Importance of Facial Features in Vision-based Sign Language Recognition: Eyes, Mouth or Full Face? cites this paper.

The Importance of Facial Features in Vision-based Sign Language Recognition: Eyes, Mouth or Full Face? Quantitative Survey of the State of the Art in Sign Language Recognition

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T13:16:01.387968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b69300d8-90a9-49e5-a5df-4e04d5944f19 · inbound

VGGT-HPE: Reframing Head Pose Estimation as Relative Pose Prediction cites this paper.

VGGT-HPE: Reframing Head Pose Estimation as Relative Pose Prediction Quantitative Survey of the State of the Art in Sign Language Recognition

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:21:01.597418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d43af086-e121-4209-a06c-f9a16a144863 · inbound

SignVerse-2M: A Two-Million-Clip Pose-Native Universe of 55+ Sign Languages cites this paper.

SignVerse-2M: A Two-Million-Clip Pose-Native Universe of 55+ Sign Languages Quantitative Survey of the State of the Art in Sign Language Recognition

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:56:04.770735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fda07174-c24f-4b2d-a230-c0eff0d22a10 · inbound

SIGMA-ASL: Sensor-Integrated Multimodal Dataset for Sign Language Recognition cites this paper.

SIGMA-ASL: Sensor-Integrated Multimodal Dataset for Sign Language Recognition Quantitative Survey of the State of the Art in Sign Language Recognition

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:06:11.252167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1cb3fa75-0bc4-4c2d-89cc-e00a400bb3d2 · inbound

Emotion Recognition in Sign Language Conversation cites this paper.

Emotion Recognition in Sign Language Conversation Quantitative Survey of the State of the Art in Sign Language Recognition

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:55:23.626235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b7f425e7-0f41-4cbb-9807-898d3dd43291 · inbound

Sign Language Recognition Using Original and Synthetic Depth Image Based Point Cloud Data Models cites this paper.

Sign Language Recognition Using Original and Synthetic Depth Image Based Point Cloud Data Models Quantitative Survey of the State of the Art in Sign Language Recognition

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T18:01:49.511890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.