Paper Citation Record · LEDGER

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech

As of 16 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2505.19446.

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

pith.paper-citation-record.v1
2505.19446 v2

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:17:35.541165Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:17:31.845764Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:17:36.289217Z

Reference resolution

44 of 44 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7c037a5b-452c-4383-bfe7-46c703e01c4f · outbound

This paper cites an unresolved cited work.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Unresolved cited work

Reference 1

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Observation 0648702d-c46d-4522-a317-a44ea1faf1ba · outbound

This paper cites Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T14:17:36.405216Z

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Observation b362a216-aefe-4530-90cc-d954e4ccd68e · outbound

This paper cites Cookie Theft.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Cookie Theft

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:43.422419Z

Source-reported events for the cited work

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Observation 131033b8-b10d-47f4-a963-7d4caeeece43 · outbound

This paper cites SIL”. Pauses at the start and end of recordings are removed. Following [29], pauses are categorized as short ( <0.5s), medium (0.5–2s), or long ( >2s), and encoded using “,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech SIL”. Pauses at the start and end of recordings are removed. Following [29], pauses are categorized as short ( <0.5s), medium (0.5–2s), or long ( >2s), and encoded using “,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:43.002803Z

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Observation 4d12fa28-eef9-4a7f-aca6-e31474720690 · outbound

This paper cites Experimental setup For the classification task, we partitioned the 157 subjects into training and validation sets in a 3:1 ratio based on diagnos- tic labels.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Experimental setup For the classification task, we partitioned the 157 subjects into training and validation sets in a 3:1 ratio based on diagnos- tic labels

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:42.631593Z

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Observation dd98ff0e-2a52-4a7b-a509-4ec5605fcb65 · outbound

This paper cites 2) On the test set, our method achieved an F1 score of 58.6%, exceed- ing the baseline (55%) by 3.6%, further confirming its effec- tiveness.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech 2) On the test set, our method achieved an F1 score of 58.6%, exceed- ing the baseline (55%) by 3.6%, further confirming its effec- tiveness

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:42.283248Z

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Observation 6675c907-68c4-4f82-8340-f56874d6e8ab · outbound

This paper cites Fine-tuned models often pre- dict MMSE scores near the mean of the training data, likely due to the dataset’s limited size (69 subjects).

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Fine-tuned models often pre- dict MMSE scores near the mean of the training data, likely due to the dataset’s limited size (69 subjects)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:42.127296Z

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Observation 2b2f8796-7179-45c4-b504-bc61c41e9c36 · outbound

This paper cites an unresolved cited work.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:17:41.973491Z

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Observation df95e73c-5362-4663-becf-83a79c7cd879 · outbound

This paper cites 23AYY012), and by the Supercomputing Center of the University of Science and Tech- nology of China.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech 23AYY012), and by the Supercomputing Center of the University of Science and Tech- nology of China

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:41.674034Z

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Observation da7584bd-4717-4a09-8af0-7d63abb8ab24 · outbound

This paper cites Dementia in the elderly: the silent epidemic,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Dementia in the elderly: the silent epidemic,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:41.371859Z

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Observation 353c4040-68f4-4f7b-8a0c-d2445717f4ad · outbound

This paper cites The alzheimer’s disease neuroimag- ing initiative (adni): Mri methods,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech The alzheimer’s disease neuroimag- ing initiative (adni): Mri methods,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:41.139657Z

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Observation a0655b2d-8e6c-4cac-8b72-16e0e8981030 · outbound

This paper cites Re- producible evaluation of classification methods in alzheimer’s dis- ease: Framework and application to mri and pet data,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Re- producible evaluation of classification methods in alzheimer’s dis- ease: Framework and application to mri and pet data,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:40.945842Z

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Observation d85633ec-3378-4b76-9dbf-e0cf2e365e28 · outbound

This paper cites Semi-supervised cognitive state classification from speech with multi-view pseudo- labeling,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Semi-supervised cognitive state classification from speech with multi-view pseudo- labeling,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:40.720410Z

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Observation 9d8d96bd-18f0-4e84-9e9d-acae395874fc · outbound

This paper cites Speech and language alter- ations in dementia syndromes,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Speech and language alter- ations in dementia syndromes,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:40.539219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1b0326fa-a289-461a-8fff-ce09dffe1e72 · outbound

This paper cites Yeung, A.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Yeung, A

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:40.375215Z

Source-reported events for the cited work

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Observation 9602a849-884c-408e-b10d-7c3e9298d442 · outbound

This paper cites De- tection of cognitive impairment and alzheimer’s disease using a speech- and language-based protocol,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech De- tection of cognitive impairment and alzheimer’s disease using a speech- and language-based protocol,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:40.208010Z

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Observation db85a939-a8eb-4995-82da-a3353b1d8189 · outbound

This paper cites Clever hans ef- fect found in automatic detection of alzheimer’s disease through speech,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Clever hans ef- fect found in automatic detection of alzheimer’s disease through speech,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:40.060074Z

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Observation babd0f16-cb1c-47c3-b851-848a49b4ed36 · outbound

This paper cites Alzheimer’s dementia detection through spontaneous dialogue with proactive robotic listeners,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Alzheimer’s dementia detection through spontaneous dialogue with proactive robotic listeners,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:39.869979Z

Source-reported events for the cited work

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Observation 89644ca9-71c7-46a1-a9e3-c2352d24b576 · outbound

This paper cites Using the outputs of different automatic speech recognition paradigms for acoustic-and BERT-based Alzheimer’s dementia detection through spontaneous speech.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Using the outputs of different automatic speech recognition paradigms for acoustic-and BERT-based Alzheimer’s dementia detection through spontaneous speech

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:39.623517Z

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Observation bd43df7a-dd43-4792-9069-86a807323481 · outbound

This paper cites Can automated speech recognition errors pro- vide valuable clues for alzheimer’s disease detection?.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Can automated speech recognition errors pro- vide valuable clues for alzheimer’s disease detection?

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:39.437128Z

Source-reported events for the cited work

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Observation 8123f0ef-f2ab-4307-bdec-54fb391594b4 · outbound

This paper cites Early Dementia Detection Using Multiple Spontaneous Speech Prompts: The PROCESS Challenge.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Early Dementia Detection Using Multiple Spontaneous Speech Prompts: The PROCESS Challenge

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:17:36.211178Z

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Observation 6365e2b1-101b-4f45-a160-4dc019ee2766 · outbound

This paper cites Alzheimer’s dementia recognition through spontaneous speech: The ADReSS challenge,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Alzheimer’s dementia recognition through spontaneous speech: The ADReSS challenge,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:39.227990Z

Source-reported events for the cited work

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Observation 18154836-1c94-4d94-8b35-6be2580ace06 · outbound

This paper cites Detecting cognitive decline using speech only: The ADReSSo Challenge.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Detecting cognitive decline using speech only: The ADReSSo Challenge

Reference 23

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Source-reported events for the cited work

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Observation 1fb9cc19-9e79-41ab-9ad5-46cc8f2d5a90 · outbound

This paper cites Multilingual Alzheimer’s dementia recogni- tion through spontaneous speech: a signal processing grand chal- lenge,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Multilingual Alzheimer’s dementia recogni- tion through spontaneous speech: a signal processing grand chal- lenge,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:39.052929Z

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Observation ffd0be5d-8d7e-4472-a06f-13f5dd4a4d85 · outbound

This paper cites Infusing acoustic pause con- text into text-based dementia assessment,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Infusing acoustic pause con- text into text-based dementia assessment,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:38.874795Z

Source-reported events for the cited work

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Observation b3edb0db-e2ad-4279-869d-7bda6320095a · outbound

This paper cites The USTC system for ADReSS-M challenge,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech The USTC system for ADReSS-M challenge,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:38.630033Z

Source-reported events for the cited work

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Observation e9f7eb3e-c67f-4662-af1a-e06b803a64fb · outbound

This paper cites Automated screening for Alzheimer’s dementia through spontaneous speech.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Automated screening for Alzheimer’s dementia through spontaneous speech

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:38.456932Z

Source-reported events for the cited work

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Observation 64648027-7545-4c35-a4d8-0e89f6edc11a · outbound

This paper cites Tackling the adresso challenge 2021: The muet-rmit system for alzheimer’s dementia recognition from spontaneous speech.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Tackling the adresso challenge 2021: The muet-rmit system for alzheimer’s dementia recognition from spontaneous speech

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:38.227404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 40a23b92-5107-4603-a695-144b86444958 · outbound

This paper cites Alzheimer's Dementia Recognition Using Acoustic, Lexical, Disfluency and Speech Pause Features Robust to Noisy Inputs.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Alzheimer's Dementia Recognition Using Acoustic, Lexical, Disfluency and Speech Pause Features Robust to Noisy Inputs

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:17:36.061435Z

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Observation db1e32de-2b39-43e7-af62-9d6252317465 · outbound

This paper cites Tackling the adress challenge: A mul- timodal approach to the automated recognition of alzheimer’s de- mentia.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Tackling the adress challenge: A mul- timodal approach to the automated recognition of alzheimer’s de- mentia

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:38.003759Z

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Observation 3f612e51-d2ef-4850-a8ae-698d1a7cdaa4 · outbound

This paper cites Alzheimer's Disease Detection from Spontaneous Speech through Combining Linguistic Complexity and (Dis)Fluency Features with Pretrained Language Models.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Alzheimer's Disease Detection from Spontaneous Speech through Combining Linguistic Complexity and (Dis)Fluency Features with Pretrained Language Models

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:17:35.874872Z

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Observation 495197e3-6695-47da-97f2-e860efddfbc6 · outbound

This paper cites Enriching Complex Networks with Word Embeddings for Detecting Mild Cognitive Impairment from Speech Transcripts.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Enriching Complex Networks with Word Embeddings for Detecting Mild Cognitive Impairment from Speech Transcripts

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:17:35.709938Z

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Observation c0b577da-ffa7-46d5-9871-da91fa952bb6 · outbound

This paper cites A comparative study of acoustic and linguistic fea- tures classification for Alzheimer’s disease detection,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech A comparative study of acoustic and linguistic fea- tures classification for Alzheimer’s disease detection,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:37.798390Z

Source-reported events for the cited work

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Observation 2ebcf7a6-d01e-44f0-8c89-211be31ff931 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 34

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Observation dd696fe6-d938-4fcc-bc4c-ea232d861fa2 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:34.816107Z

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Observation 369cda22-f27b-420b-97ea-283e6aac4253 · outbound

This paper cites Ernie 2.0: A continual pre-training framework for language un- derstanding,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Ernie 2.0: A continual pre-training framework for language un- derstanding,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:37.679268Z

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Observation 8f1f1783-3b71-4d47-bb5b-e8348b215aa4 · outbound

This paper cites Exploring linguistic feature and model combination for speech recognition based automatic ad detection,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Exploring linguistic feature and model combination for speech recognition based automatic ad detection,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:37.463583Z

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Observation 339ce8c5-aaae-4913-828e-c853ab7fe87e · outbound

This paper cites Disflu- encies and fine-tuning pre-trained language models for detection of Alzheimer’s disease.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Disflu- encies and fine-tuning pre-trained language models for detection of Alzheimer’s disease

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:37.221254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e94bc346-b182-410e-8aa5-7b9ba493fecb · outbound

This paper cites Mp-senet: A speech enhance- ment model with parallel denoising of magnitude and phase spec- tra,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Mp-senet: A speech enhance- ment model with parallel denoising of magnitude and phase spec- tra,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:37.019156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9e6686eb-0df9-40e3-9a53-551f93db1be0 · outbound

This paper cites Leveraging prompt learning and pause encoding for alzheimer’s disease de- tection,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Leveraging prompt learning and pause encoding for alzheimer’s disease de- tection,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:36.838220Z

Source-reported events for the cited work

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Observation 95df7df4-4007-4650-828f-7011cbe82e90 · outbound

This paper cites Powerset multi-class cross entropy loss for neural speaker diarization,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Powerset multi-class cross entropy loss for neural speaker diarization,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:35.311990Z

Source-reported events for the cited work

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Observation 1a2231e4-1256-46f1-9453-9c6661497c0c · outbound

This paper cites Speaker identification on the scotus corpus,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Speaker identification on the scotus corpus,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:36.698145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 46b824c8-adb5-4b7d-ab83-5bd2b7de3550 · outbound

This paper cites Attention is all you need,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech Attention is all you need,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:35.465828Z

Source-reported events for the cited work

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Observation e3170ee5-dbac-42df-81b0-774bf3f6784d · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representa- tions,.

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech wav2vec 2.0: A framework for self-supervised learning of speech representa- tions,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:17:36.556295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation 0648702d-c46d-4522-a317-a44ea1faf1ba · inbound