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Paper Citation Record · LEDGER

Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2101.08533.

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

pith.paper-citation-record.v1
2101.08533 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:47:50.362206Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T00:03:39.395059Z

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 a0d88e03-505e-4bb4-9b7c-e51132615001 · inbound

Pose-dIVE: Pose-Diversified Augmentation with Diffusion Model for Person Re-Identification cites this paper.

Pose-dIVE: Pose-Diversified Augmentation with Diffusion Model for Person Re-Identification Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-24T00:03:39.397217Z

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.

source=arxiv_source observed=2026-05-23T23:59:50.234766Z digest=sha256:9490513fd46b060e05344ac598b9833d271ed0d719535a30f90cd0aab57b1cc2

Observation 2a59e8b0-f24f-41d5-bd05-2840cc8bee1f · inbound

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency cites this paper.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:50.362206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:50.362206Z digest=sha256:91838a0c431736f540afa05e612565f51b54e0045315bff9606c14f08c943d8d

Observation 6f04da94-1dda-4e8a-869b-7f4d806193fe · inbound

Cross-modal Ship Re-Identification via Optical and SAR Imagery: A Novel Dataset and Method cites this paper.

Cross-modal Ship Re-Identification via Optical and SAR Imagery: A Novel Dataset and Method Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T22:17:38.553922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:17:38.553922Z digest=sha256:718c8d1ad6f8e1e76c33424cc7a24cf5837fd6e26473f996a90e68bde507f332

Observation 1e9c1c87-6de6-4054-8d2a-ff528d4fa347 · inbound

FADE: Adversarial Concept Erasure in Flow Models cites this paper.

FADE: Adversarial Concept Erasure in Flow Models Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-06T17:00:00.346876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:00:00.346876Z digest=sha256:aa000e0eabfa699d4c92729078373729c15fcfb54b4c51f138f266ba0a7f44aa

Observation 7dc80e75-3ada-4bcf-a999-76d8298b3db0 · inbound

Decoupled Spatio-Temporal Consistency Learning for Self-Supervised Tracking cites this paper.

Decoupled Spatio-Temporal Consistency Learning for Self-Supervised Tracking Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T12:41:51.272488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:41:51.272488Z digest=sha256:9e6bd9c4ee0cb19318801c10d30d68355a3b49c41404786ccef7d5949a92d2e0