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Paper Citation Record · LEDGER

ViPE: Visualise Pretty-much Everything

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.10543.

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

pith.paper-citation-record.v1
2310.10543 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:37:54.858970Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T16:42:43.857075Z

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 0573cd78-9f8f-45af-9da6-c600d147b51e · inbound

FluentAvatar: Flicker-Free Talking-Head Animation via Phoneme-Guided Autoregressive Modeling cites this paper.

FluentAvatar: Flicker-Free Talking-Head Animation via Phoneme-Guided Autoregressive Modeling ViPE: Visualise Pretty-much Everything

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-18T16:42:43.860664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-18T16:42:25.803856Z digest=sha256:cf3443402e6dd2cd120cb4bc62aa84d2b98ebe0aed7b8655b9b0683b627e6acc

Observation 5dd47e9d-764c-4cf3-8b52-4873c728473d · inbound

Computational Humor with Multimodal LLMs: Methods, Datasets, Evaluation, and Challenges cites this paper.

Computational Humor with Multimodal LLMs: Methods, Datasets, Evaluation, and Challenges ViPE: Visualise Pretty-much Everything

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-15T15:37:54.858970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:37:54.858970Z digest=sha256:47d7ff9f73426df54e9238b37089dcb99515a301e511cfa8873100be890ef68d