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Paper Citation Record · LEDGER

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2210.08340.

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

pith.paper-citation-record.v1
2210.08340 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:16:48.684752Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T20:24:02.197720Z

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 72ff50b4-6387-4dcb-b263-0c10b340d142 · inbound

The Generalist Brain Module: Module Repetition in Neural Networks in Light of the Minicolumn Hypothesis cites this paper.

The Generalist Brain Module: Module Repetition in Neural Networks in Light of the Minicolumn Hypothesis Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

Reference 101

Resolution
unresolved
no resolver link, observed 2026-08-06T21:16:48.684752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:16:48.684752Z digest=sha256:7a920e1688a177b0cbf7b921471cff26cbe698dcd58db6ae492f8fb3fe1a0850

Observation d29d846c-ba13-49c1-83e7-faff9fb5a524 · inbound

Generalizable and Computational Efficient Channel Extrapolation for 6G: A Configurable AI-Driven Framework Built from a Modular Perspective cites this paper.

Generalizable and Computational Efficient Channel Extrapolation for 6G: A Configurable AI-Driven Framework Built from a Modular Perspective Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

Reference 49

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:24:02.280440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T20:24:00.540463Z digest=sha256:6c7c46e0075dae37360a63ab9ca14c9f0e3b2cdc430a1b53b0edea07dafd756a