Paper Citation Record · LEDGER

Decoding individual words from non-invasive brain recordings across 723 participants

As of 15 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 2 inbound Pith citation observations for arXiv:2412.17829.

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

pith.paper-citation-record.v1
2412.17829 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

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measured 64 of 64 standing notices

One-hop event checks from named stored sources.

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:37:51.892847Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:40:02.272934Z

Reference resolution

62 of 62 outbound references displayed

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External citation measurements

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Outbound references

Observation ec6a3bed-8a6a-4725-95a5-2ba9af76962d · outbound

This paper cites an unresolved cited work.

Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

Reference 1

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Observation 5ab028d6-5d1a-453a-978f-7f803dabab6b · outbound

This paper cites Journal of neural engineering16, 036019 (2019).

Decoding individual words from non-invasive brain recordings across 723 participants Journal of neural engineering16, 036019 (2019)

Reference 2

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This paper cites K., Chartier, J.

Decoding individual words from non-invasive brain recordings across 723 participants K., Chartier, J

Reference 3

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This paper cites L.et al.A high-performance neuropros- thesis for speech decoding and avatar control.Nature 620, 1037–1046 (2023).

Decoding individual words from non-invasive brain recordings across 723 participants L.et al.A high-performance neuropros- thesis for speech decoding and avatar control.Nature 620, 1037–1046 (2023)

Reference 4

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

Reference 5

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Observation 69224ba4-8109-4af4-8e3c-3c8297b21df2 · outbound

This paper cites R.et al.A high-performance speech neu- roprosthesis.

Decoding individual words from non-invasive brain recordings across 723 participants R.et al.A high-performance speech neu- roprosthesis

Reference 6

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This paper cites bioRxiv, 2024–08 (2024).

Decoding individual words from non-invasive brain recordings across 723 participants bioRxiv, 2024–08 (2024)

Reference 7

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This paper cites S.et al.An accurate and rapidly calibrat- ing speech neuroprosthesis.New England Journal of Medicine 391, 609–618 (2024).

Decoding individual words from non-invasive brain recordings across 723 participants S.et al.An accurate and rapidly calibrat- ing speech neuroprosthesis.New England Journal of Medicine 391, 609–618 (2024)

Reference 8

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

Reference 9

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Observation 0b5967ab-e751-472c-9535-b2d6176df4ea · outbound

This paper cites M.et al.Detecting awareness in the vege- tative state.science 313, 1402–1402 (2006).

Decoding individual words from non-invasive brain recordings across 723 participants M.et al.Detecting awareness in the vege- tative state.science 313, 1402–1402 (2006)

Reference 10

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

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This paper cites G.et al.Cognitive Motor Dissociation in Disorders of Consciousness.New England Journal of Medicine 391, 598–608 (2024).

Decoding individual words from non-invasive brain recordings across 723 participants G.et al.Cognitive Motor Dissociation in Disorders of Consciousness.New England Journal of Medicine 391, 598–608 (2024)

Reference 13

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This paper cites W., Jiang, Y.

Decoding individual words from non-invasive brain recordings across 723 participants W., Jiang, Y

Reference 14

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This paper cites & Priftis, K.

Decoding individual words from non-invasive brain recordings across 723 participants & Priftis, K

Reference 15

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Decoding individual words from non-invasive brain recordings across 723 participants & Huth, A

Reference 16

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Decoding individual words from non-invasive brain recordings across 723 participants & King, J.-R

Reference 17

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This paper cites M.et al.Predicting human brain activity associated with the meanings of nouns.science 320, 1191–1195 (2008).

Decoding individual words from non-invasive brain recordings across 723 participants M.et al.Predicting human brain activity associated with the meanings of nouns.science 320, 1191–1195 (2008)

Reference 18

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This paper cites & King, J.-R.

Decoding individual words from non-invasive brain recordings across 723 participants & King, J.-R

Reference 19

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This paper cites Brain embeddings with shared geometry to artificial contextual embeddings, as a code for representing language in the human brain.

Decoding individual words from non-invasive brain recordings across 723 participants Brain embeddings with shared geometry to artificial contextual embeddings, as a code for representing language in the human brain

Reference 20

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This paper cites S.et al.Large-scale replication study reveals a limit on probabilistic prediction in language comprehension.

Decoding individual words from non-invasive brain recordings across 723 participants S.et al.Large-scale replication study reveals a limit on probabilistic prediction in language comprehension

Reference 21

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This paper cites P., Anderson, A.

Decoding individual words from non-invasive brain recordings across 723 participants P., Anderson, A

Reference 22

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This paper cites bioRxiv,2023.07.24.550310.

Decoding individual words from non-invasive brain recordings across 723 participants bioRxiv,2023.07.24.550310

Reference 23

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

Reference 24

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This paper cites & Schoffe- len, J.-M.

Decoding individual words from non-invasive brain recordings across 723 participants & Schoffe- len, J.-M

Reference 25

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

Reference 26

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This paper cites Learning transferable visual models from natural language supervisionin International conference on machine learning(2021), 8748–8763.

Decoding individual words from non-invasive brain recordings across 723 participants Learning transferable visual models from natural language supervisionin International conference on machine learning(2021), 8748–8763

Reference 27

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This paper cites Sigmoid Loss for Language Image Pre-Training.

Decoding individual words from non-invasive brain recordings across 723 participants Sigmoid Loss for Language Image Pre-Training

Reference 28

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

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This paper cites J.et al.EEGNet: a compact convolu- tional neural network for EEG-based brain–computer interfaces.

Decoding individual words from non-invasive brain recordings across 723 participants J.et al.EEGNet: a compact convolu- tional neural network for EEG-based brain–computer interfaces

Reference 30

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

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This paper cites WhisperX: Time-Accurate Speech Transcription of Long-Form Audio.

Decoding individual words from non-invasive brain recordings across 723 participants WhisperX: Time-Accurate Speech Transcription of Long-Form Audio

Reference 32

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

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Decoding individual words from non-invasive brain recordings across 723 participants Are EEG-to-Text Models Working?

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

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This paper cites Decoupled Weight Decay Regularization.

Decoding individual words from non-invasive brain recordings across 723 participants Decoupled Weight Decay Regularization

Reference 37

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

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Decoding individual words from non-invasive brain recordings across 723 participants & King, J.-R

Reference 39

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This paper cites & Poesio, M.Detecting semantic category in simultaneous EEG/MEG recordingsin Proceedings of the naacl hlt 2010 first workshop on computational neurolinguistics (2010), 36–44.

Decoding individual words from non-invasive brain recordings across 723 participants & Poesio, M.Detecting semantic category in simultaneous EEG/MEG recordingsin Proceedings of the naacl hlt 2010 first workshop on computational neurolinguistics (2010), 36–44

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:50:18.061963Z

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This paper cites Advances in Neural Information Processing Sys- tems 36 (2024).

Decoding individual words from non-invasive brain recordings across 723 participants Advances in Neural Information Processing Sys- tems 36 (2024)

Reference 41

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

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This paper cites arXiv preprint arXiv:2311.09889(2023).

Decoding individual words from non-invasive brain recordings across 723 participants arXiv preprint arXiv:2311.09889(2023)

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Observation 2cdf1e00-80b5-4997-a9b3-6b462f049810 · outbound

This paper cites Open-vocabulary Auditory Neural Decoding Using fMRI-prompted LLM.

Decoding individual words from non-invasive brain recordings across 723 participants Open-vocabulary Auditory Neural Decoding Using fMRI-prompted LLM

Reference 45

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Decoding individual words from non-invasive brain recordings across 723 participants Language Reconstruction with Brain Predictive Coding from fMRI Data

Reference 46

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Decoding individual words from non-invasive brain recordings across 723 participants UniCoRN: Unified Cognitive Signal ReconstructioN bridging cognitive signals and human language

Reference 47

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

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Observation 56f1bc56-7ae9-473c-ab79-a2f1c4be387e · outbound

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Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

Reference 49

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Observation 4b6a4b13-9aeb-48ea-a6b3-b3749b6debcd · outbound

This paper cites R.et al.Toward a brain-based componen- tial semantic representation.Cognitive neuropsychol- ogy 33, 130–174 (2016).

Decoding individual words from non-invasive brain recordings across 723 participants R.et al.Toward a brain-based componen- tial semantic representation.Cognitive neuropsychol- ogy 33, 130–174 (2016)

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:50:17.964050Z

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Observation e5f3ee40-954d-4f1c-bf04-1d88cfd110ea · outbound

This paper cites G., De Heer, W.

Decoding individual words from non-invasive brain recordings across 723 participants G., De Heer, W

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:50:17.945820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ba98c7c2-8308-4800-85c8-0982d3617cd5 · outbound

This paper cites an unresolved cited work.

Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-11T17:50:17.929256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2048c40e-cf9a-4a6b-9710-42fe0137b075 · outbound

This paper cites an unresolved cited work.

Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-11T17:50:17.913322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e88d7c5d-7666-419d-b6ea-e32d27849e02 · outbound

This paper cites & Huth, A.

Decoding individual words from non-invasive brain recordings across 723 participants & Huth, A

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:50:17.893782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1a5e0640-82d0-483b-9359-e467283b5761 · outbound

This paper cites Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects.

Decoding individual words from non-invasive brain recordings across 723 participants Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-11T17:50:17.265289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4c41ae1-7505-41d8-aa2a-5c060e4b4d15 · outbound

This paper cites & King, J.-R.

Decoding individual words from non-invasive brain recordings across 723 participants & King, J.-R

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:50:17.876370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 176c6fe9-fb46-4ba4-8613-1e185b8721e5 · outbound

This paper cites Toward a realistic model of speech processing in the brain with self-supervised learning.

Decoding individual words from non-invasive brain recordings across 723 participants Toward a realistic model of speech processing in the brain with self-supervised learning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:50:17.848891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 51a63f0d-2d4e-401b-9669-2548a3ec54e5 · outbound

This paper cites an unresolved cited work.

Decoding individual words from non-invasive brain recordings across 723 participants Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-11T17:50:17.827106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3deccc00-ead7-4c76-b0aa-80a3c3feb36f · outbound

This paper cites & Mitchell, T.

Decoding individual words from non-invasive brain recordings across 723 participants & Mitchell, T

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:50:17.802932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9f2f6b49-8d9a-40bd-8330-34304eecad7f · outbound

This paper cites F.et al.Decoding spoken phonemes from sensorimotor cortex with high-density ECoG grids.

Decoding individual words from non-invasive brain recordings across 723 participants F.et al.Decoding spoken phonemes from sensorimotor cortex with high-density ECoG grids

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:50:17.785944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5bd0a663-e419-49c3-a6f1-ede2b9bdbdf2 · outbound

This paper cites G., Moses, D.

Decoding individual words from non-invasive brain recordings across 723 participants G., Moses, D

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:50:17.763350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 709dd3a6-c9ed-4a42-bf4b-c6e8eede56e6 · outbound

This paper cites Decoding Chinese phonemes from intracortical brain signals with hyperbolic-space neural representations.

Decoding individual words from non-invasive brain recordings across 723 participants Decoding Chinese phonemes from intracortical brain signals with hyperbolic-space neural representations

Reference 62

Resolution: malformed identifier; local_arxiv, observed 2026-08-11T17:50:17.354453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation 632eb825-2cd7-4184-98fa-c243180d2383 · inbound

Dynadiff: Single-stage Decoding of Images from Continuously Evolving fMRI cites this paper.

Dynadiff: Single-stage Decoding of Images from Continuously Evolving fMRI Decoding individual words from non-invasive brain recordings across 723 participants

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:51.892847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e975fe0-8199-46ec-a71a-d4450d727c44 · inbound

The 2025 PNPL Competition: Speech Detection and Phoneme Classification in the LibriBrain Dataset cites this paper.

The 2025 PNPL Competition: Speech Detection and Phoneme Classification in the LibriBrain Dataset Decoding individual words from non-invasive brain recordings across 723 participants

Reference 2024

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:40:02.385647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.