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Paper Citation Record · LEDGER

On Computational Limits and Provably Efficient Criteria of Visual Autoregressive Models: A Fine-Grained Complexity Analysis

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2501.04377.

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

pith.paper-citation-record.v1
2501.04377 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:43:27.628258Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T06:26:27.600677Z

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 b4c53871-a608-4c6e-a2b8-531d646177a5 · inbound

T2VWorldBench: A Benchmark for Evaluating World Knowledge in Text-to-Video Generation cites this paper.

T2VWorldBench: A Benchmark for Evaluating World Knowledge in Text-to-Video Generation On Computational Limits and Provably Efficient Criteria of Visual Autoregressive Models: A Fine-Grained Complexity Analysis

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T14:43:27.628258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:43:27.628258Z digest=sha256:755c0612aea95937a5b6e7fd4f9d15a2a19c2930e01cb495bfefdda4277910d1

Observation 372befcb-6b67-4192-ab97-fad09255e74c · inbound

Depth Adaptive Efficient Visual Autoregressive Modeling cites this paper.

Depth Adaptive Efficient Visual Autoregressive Modeling On Computational Limits and Provably Efficient Criteria of Visual Autoregressive Models: A Fine-Grained Complexity Analysis

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:26:27.602083Z

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=pdf_text observed=2026-05-10T06:22:55.035749Z digest=sha256:267c846894acee8e80422cfb2d58f8afe4ebf5ed2a64b2c35aa5d6e04d44529e