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Paper Citation Record · LEDGER

CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2401.18075.

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

pith.paper-citation-record.v1
2401.18075 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:04:03.508252Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T13:04:03.599085Z

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 2617d299-2174-4da8-85e4-f31707201c2d · inbound

Multi-View Pedestrian Occupancy Prediction with a Novel Synthetic Dataset cites this paper.

Multi-View Pedestrian Occupancy Prediction with a Novel Synthetic Dataset CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting

Reference 52

Resolution
verified exact
local_arxiv, observed 2026-08-11T13:04:03.605490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T13:04:03.508252Z digest=sha256:71fd6406eeb9ab904a83b105479eae65185e184af48e9196ce3e90a6a92074e5