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Paper Citation Record · LEDGER

Decoding speech perception from non-invasive brain recordings

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2208.12266.

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

pith.paper-citation-record.v1
2208.12266 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:40:18.640382Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T02:49:25.391649Z

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 9f942eed-5fed-4c43-97d2-366cb839f4a7 · inbound

Optimizing fMRI Data Acquisition for Decoding Natural Speech with Limited Participants cites this paper.

Optimizing fMRI Data Acquisition for Decoding Natural Speech with Limited Participants Decoding speech perception from non-invasive brain recordings

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T13:40:18.640382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:40:18.640382Z digest=sha256:7d4a1f9a5516e344e063e8a604238ac55009ffa50281410a25ccd37c447d4e41

Observation eb09cb0c-f9e4-4089-a037-13256eb6bb10 · inbound

Neuro2Semantic: A Transfer Learning Framework for Semantic Reconstruction of Continuous Language from Human Intracranial EEG cites this paper.

Neuro2Semantic: A Transfer Learning Framework for Semantic Reconstruction of Continuous Language from Human Intracranial EEG Decoding speech perception from non-invasive brain recordings

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T12:11:11.607930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:11:11.607930Z digest=sha256:dcd9c1ec9696033d8ff85b9878214104d5423a3cd94ac29c4df7cbe5d0e2923e

Observation 598e9584-1235-43a8-afdc-a5936954bb03 · inbound

NeuralBench: A Unifying Framework to Benchmark NeuroAI Models cites this paper.

NeuralBench: A Unifying Framework to Benchmark NeuroAI Models Decoding speech perception from non-invasive brain recordings

Reference 249

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:16:15.686175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T02:16:10.680353Z digest=sha256:b48c580029ac9d21affb55243eb9617281ab17c95cd8e3d116562fe199235a0e

Observation c7d1d2b8-4bda-4d8d-aadf-2ffb81e316f5 · inbound

Can neurons speak? Semantic narration of vision at single-cell resolution cites this paper.

Can neurons speak? Semantic narration of vision at single-cell resolution Decoding speech perception from non-invasive brain recordings

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-04T02:49:25.393207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T18:52:22.357765Z digest=sha256:5c4acbc76eac3625a3576be5a60d56c8bb3ffe3ff8d3705efcf72294440dd46b

Observation 1a8f79fa-a91b-4549-9018-5166a4c5f002 · inbound

Toward Annotation-Efficient Continuous Emotion Arousal Quantification via Group-Level EEG Dynamic Neural Synchrony cites this paper.

Toward Annotation-Efficient Continuous Emotion Arousal Quantification via Group-Level EEG Dynamic Neural Synchrony Decoding speech perception from non-invasive brain recordings

Reference 111

Resolution
unresolved
no resolver link, observed 2026-07-31T14:47:01.843480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T14:47:01.843480Z digest=sha256:62763b00824341827bb2eadda77d796147abae8f11b20462aa0b11f5c941d988