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Paper Citation Record · LEDGER

PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.11421.

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

pith.paper-citation-record.v1
2305.11421 v3

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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:55:10.128731Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T19:55:10.192769Z

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 812dfe92-d89b-4203-834f-2ab7a377edfd · inbound

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing cites this paper.

STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction

Reference 49

Resolution
verified exact
local_arxiv, observed 2026-08-12T19:55:10.198506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:55:10.128731Z digest=sha256:b5fc63f7c1c93a60d58252313a75d8a09ba301cd03e65fe5a6de87640f460ba6

Observation 8ef90ae2-f698-4bfc-bfae-d23f77603f63 · inbound

Generative Physical AI in Vision: A Survey cites this paper.

Generative Physical AI in Vision: A Survey PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-10T18:53:00.238382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:53:00.238382Z digest=sha256:d928dd44d42c946c22dc770997b4604cfd6d08a80b9eacea77db60bfa63e5b87