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Paper Citation Record · LEDGER

Unleashing the Power of CNN and Transformer for Balanced RGB-Event Video Recognition

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.11128.

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

pith.paper-citation-record.v1
2312.11128 v2

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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:42:24.226239Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T16:35:42.330835Z

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 9b8d224f-d4f0-4319-83f2-bf9ba0579ef9 · inbound

EventCrab: Harnessing Frame and Point Synergy for Event-based Action Recognition and Beyond cites this paper.

EventCrab: Harnessing Frame and Point Synergy for Event-based Action Recognition and Beyond Unleashing the Power of CNN and Transformer for Balanced RGB-Event Video Recognition

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-23T16:35:42.333920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-23T16:33:11.271072Z digest=sha256:41cdd3c62a629d32da095ec806ce38011ea461ffbf172d0fab001ab208c90f76

Observation f557a417-ee95-4478-b0a2-e1de5ceeecaf · inbound

VELoRA: A Low-Rank Adaptation Approach for Efficient RGB-Event based Recognition cites this paper.

VELoRA: A Low-Rank Adaptation Approach for Efficient RGB-Event based Recognition Unleashing the Power of CNN and Transformer for Balanced RGB-Event Video Recognition

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-10T23:42:24.226239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:42:24.226239Z digest=sha256:a9d40f640ce4e44ec83f5834c19d8d2b171e5a863282bdb7791e732c30aea6ec