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Paper Citation Record · LEDGER

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming

As of 22 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2505.10536.

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

pith.paper-citation-record.v1
2505.10536 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:14:36.289737Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

  • verified exact2
  • verified fuzzy4
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 72952450-a9e9-4f74-8099-a7b562d0b503 · outbound

This paper cites Effects of padding on LSTMs and CNNs.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Effects of padding on LSTMs and CNNs

Reference 4

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unresolved
no resolver link, observed 2026-08-15T21:14:36.240330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:36.240330Z digest=sha256:56e9b346d67eb40e5d42f8d1efc787782829d8cb45be40f52d66e89ea982b0ad

Observation 966a4e40-bf05-4dd0-9fce-a474d2efdfc3 · outbound

This paper cites Agency Perception and Brain Synchrony: A Hyperscanning Study of Human-Human and Human-AI Interaction.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Agency Perception and Brain Synchrony: A Hyperscanning Study of Human-Human and Human-AI Interaction

Reference 5

Resolution
metadata mismatch
local_arxiv, observed 2026-08-15T21:14:36.424377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:14:36.245835Z digest=sha256:24e0d8b1303467c65d3c324be05d2efcdbd69ce15b0f00b5f6e338da617249da

Observation 337d7e9b-4643-46c1-a20a-171186648ea6 · outbound

This paper cites Assessing Generalization of SGD via Disagreement.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Assessing Generalization of SGD via Disagreement

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:36.259687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:36.259687Z digest=sha256:9f9e53aa68f6820d6e1a835796bfb3aade374df32c9452447254a877ffa58404

Observation 22defe09-b4b0-43e4-8f55-952bb1cb0504 · outbound

This paper cites Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-15T21:14:36.382419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:14:36.264006Z digest=sha256:44f02735be391a30bccb43ef3d698560b0812937b60bcb243e079a6ccea11c2a

Observation db205f69-9ffa-48f1-9c4a-5073c3b5ee10 · outbound

This paper cites News Recommendation with Attention Mechanism.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming News Recommendation with Attention Mechanism

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-15T21:14:36.365879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:14:36.269018Z digest=sha256:1a40281cb51bcec52da152d4f9b78bad273161ece83a772cab358a4342476db4

Observation c2b2936c-2d5d-4278-9ca3-26c2e0a639f5 · outbound

This paper cites Imaging Time-Series to Improve Classification and Imputation.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Imaging Time-Series to Improve Classification and Imputation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:36.285841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:36.285841Z digest=sha256:12bfb8ddae25e3ac9566a75607aec6dc9b2f273ad6750a78bf40da18a4becf02

Observation 390e4745-62d1-46cb-991b-ada0bc15cc7c · outbound

This paper cites A hybrid gcn and filter-based framework for channel and feature selection: An fnirs-bci study.International Journal of Intelligent Systems, 2023(1):8812844,.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming A hybrid gcn and filter-based framework for channel and feature selection: An fnirs-bci study.International Journal of Intelligent Systems, 2023(1):8812844,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-15T21:14:36.471037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:14:36.289737Z digest=sha256:5f78658fde740726aec2b4b27d18d1a00b81454fec10017a95dbcee5ec5fbbdf

Observation 4e224837-e798-442c-ac5b-dbe35b07589c · outbound

This paper cites Quantifying mental workload of operators performing n-back working memory task: 28 Toward fnirs based passive bci system.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Quantifying mental workload of operators performing n-back working memory task: 28 Toward fnirs based passive bci system

Reference 2004

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:36.507802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:14:36.236308Z digest=sha256:b55f0538f355fd5208bf1508998e33a9d73e882474b4faa0528d4b153a2c38a1

Observation a23c42ec-1275-43b0-8b3c-2bfe6edc9c9e · outbound

This paper cites Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI

Reference 2006

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unresolved
no resolver link, observed 2026-08-15T21:14:36.255029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:36.255029Z digest=sha256:6b024284fcac010fa6ddd2fd8404903c04fa64d8fa0306e4f706a9034aa61b6b

Observation fb112453-492a-4293-be63-3c458a7b2cdd · outbound

This paper cites A Survey on the Robustness of Feature Importance and Counterfactual Explanations.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming A Survey on the Robustness of Feature Importance and Counterfactual Explanations

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:36.273410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:36.273410Z digest=sha256:0c092ac60c281d7486d2411b536fc0898e202c3146f66c81410ead462b1193cf

Observation 280400ed-902c-443b-8a31-407458af54b8 · outbound

This paper cites Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:36.231599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:36.231599Z digest=sha256:df1bdfbea1dde0a768955d495bb57ccbaee7770b799353f844b9e3966600d2f5

Observation 7284c5e0-faa1-44e9-ab26-6ff012aa4369 · outbound

This paper cites Random forest algorithm overview.Babylonian Journal of Machine Learning, 2024:69–79,.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Random forest algorithm overview.Babylonian Journal of Machine Learning, 2024:69–79,

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:36.483143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:14:36.281875Z digest=sha256:d670baf7935f8a2eab90f726ad790f0839428bb3dec0b49172d4cf79633b573b

Observation 7bbab458-753f-4bce-98b2-a3a466f5f875 · outbound

This paper cites Deep Learning using Rectified Linear Units (ReLU).

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Deep Learning using Rectified Linear Units (ReLU)

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:36.226893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:36.226893Z digest=sha256:29be47f8caafb76d6044f62cc81114ca0a20f54f09acc4f6c3034b8da28df2ec

Observation d29ff7d7-00ad-4962-b427-3c8c4c4930fa · outbound

This paper cites Understanding Softmax Confidence and Uncertainty.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Understanding Softmax Confidence and Uncertainty

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:36.276814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:36.276814Z digest=sha256:7e908c92ffa66e41977cf96929f0ef63c3faebe63d46ad25b3acdd3bbfa4542c

Observation 8b5723c2-d3af-4ac8-bdfd-b21cf4dc7f81 · outbound

This paper cites Knn model-based approach in classification.

Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming Knn model-based approach in classification

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:14:36.495534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:14:36.250651Z digest=sha256:3e8f1d0cef2176d779a00e813e2b73da418a1c127d89de7db128af10047ab9e3

Pith citing papers

No inbound Pith citation observations are available.