Paper Citation Record · LEDGER

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning

As of 27 July 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2606.17254.

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

pith.paper-citation-record.v1
2606.17254 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T02:26:24.653249Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-27T06:30:09.085275+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T02:26:24.653249Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T18:38:50.047471Z

Reference resolution

38 of 38 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 038342b3-2287-4c35-87ec-e3e88259c053 · outbound

This paper cites Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning

Reference 1

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Observation f8a74288-518b-4dfe-8efa-7f6c719a3b35 · outbound

This paper cites Whisper (base)[14], a 74M-parameter encoder–decoder Transformer trained on∼680k hours of weakly supervised, diverse audio.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Whisper (base)[14], a 74M-parameter encoder–decoder Transformer trained on∼680k hours of weakly supervised, diverse audio

Reference 2

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Observation d0b06928-743b-4f8f-aa39-20ea8377fd86 · outbound

This paper cites The CNN uses two convolution layers (64 and 128 filters, kernel.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning The CNN uses two convolution layers (64 and 128 filters, kernel

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-27T02:26:24.653249Z

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Observation dc17bc7c-d369-4a3a-8848-ec88370affbd · outbound

This paper cites com/Helixometry/ORBIT.git.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning com/Helixometry/ORBIT.git

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-27T02:26:24.653249Z

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Observation 40afba8c-1a7d-41b0-986f-a535d80b5bf4 · outbound

This paper cites Dataset We construct a multilingual corpus covering four languages (English, Chinese, Spanish, Greek) for ADD using publicly available resources.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Dataset We construct a multilingual corpus covering four languages (English, Chinese, Spanish, Greek) for ADD using publicly available resources

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-27T02:26:24.653249Z

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Observation 4c67564e-b315-4472-937c-3fe64c2a3145 · outbound

This paper cites Multilingual speech and text encoders cap- ture complementary acoustic–linguistic markers of impairment, but strong transfer requires explicitly suppressing language- specific cues.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Multilingual speech and text encoders cap- ture complementary acoustic–linguistic markers of impairment, but strong transfer requires explicitly suppressing language- specific cues

Reference 6

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Observation cb3bad79-d155-455a-b246-5fa6580df7c2 · outbound

This paper cites an unresolved cited work.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Unresolved cited work

Reference 7

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Observation e624b3d0-4eaa-4eb5-9a0f-bf4798b36a0a · outbound

This paper cites It did not affect the study’s ideas, analyses, results, or interpretation.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning It did not affect the study’s ideas, analyses, results, or interpretation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-27T02:26:24.653249Z

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Observation 8bf26985-8189-4f3a-8983-4e0cd9ff21bf · outbound

This paper cites Alzheimer’s Dementia Recognition Through Spontaneous Speech: The ADReSS Challenge,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Alzheimer’s Dementia Recognition Through Spontaneous Speech: The ADReSS Challenge,

Reference 9

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Observation a96ac924-8073-411f-86fa-f235e1ba4700 · outbound

This paper cites Detecting Cognitive Decline Using Speech Only: The ADReSSo Challenge,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Detecting Cognitive Decline Using Speech Only: The ADReSSo Challenge,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-27T02:26:24.653249Z

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Observation 5a20f326-cfad-4c66-84bc-f3c6d809b579 · outbound

This paper cites Detecting linguistic charac- teristics of alzheimer’s dementia by interpreting neural models,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Detecting linguistic charac- teristics of alzheimer’s dementia by interpreting neural models,

Reference 11

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Observation a1c592e5-0592-497b-8904-3c1cecd86080 · outbound

This paper cites Speech-based auto- mated cognitive status assessment,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Speech-based auto- mated cognitive status assessment,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-27T02:26:24.653249Z

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Observation ef28cf42-beca-4e90-a199-1a717eb8b54f · outbound

This paper cites Digital technologies as biomarkers, clinical out- comes assessment, and recruitment tools in alzheimer’s disease clinical trials,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Digital technologies as biomarkers, clinical out- comes assessment, and recruitment tools in alzheimer’s disease clinical trials,

Reference 13

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Observation 9e1628dd-b544-4b1d-843d-b97dd4d4dbac · outbound

This paper cites Detecting Mild Cognitive Impairment from Spontaneous Speech by Correlation- Based Phonetic Feature Selection,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Detecting Mild Cognitive Impairment from Spontaneous Speech by Correlation- Based Phonetic Feature Selection,

Reference 14

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Observation 863899e3-96aa-4671-9a32-3e82cfb4ae9d · outbound

This paper cites Investigat- ing the Effect of Audio Duration on Dementia Detection Using Acoustic Features,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Investigat- ing the Effect of Audio Duration on Dementia Detection Using Acoustic Features,

Reference 15

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Observation 3e48ba1a-90d8-4c72-88f6-5a0c6d5f614d · outbound

This paper cites Detecting Alzheimer’s Dis- ease Using Interactional and Acoustic Features from Spontaneous Speech,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Detecting Alzheimer’s Dis- ease Using Interactional and Acoustic Features from Spontaneous Speech,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-27T02:26:24.653249Z

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Observation a8ea3a77-336b-408c-8ce7-aaefde7257f7 · outbound

This paper cites Detecting Alzheimer’s Disease Using Gated Convolutional Neural Network from Audio Data,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Detecting Alzheimer’s Disease Using Gated Convolutional Neural Network from Audio Data,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-27T02:26:24.653249Z

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Observation 9d59c48a-2d1a-4e84-a406-ad4ad873cec4 · outbound

This paper cites Multi-Modal Fusion with Gating Using Audio, Lexical and Disfluency Features for Alzheimer’s Dementia Recognition from Spontaneous Speech,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Multi-Modal Fusion with Gating Using Audio, Lexical and Disfluency Features for Alzheimer’s Dementia Recognition from Spontaneous Speech,

Reference 18

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Observation 4f8478f6-f9f3-48c0-9c5c-4c8e6c19d8db · outbound

This paper cites Alzheimer’s Dementia Recognition Using Acoustic, Lex- ical, Disfluency and Speech Pause Features Robust to Noisy In- puts,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Alzheimer’s Dementia Recognition Using Acoustic, Lex- ical, Disfluency and Speech Pause Features Robust to Noisy In- puts,

Reference 19

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Observation 388e32dc-7a93-43ba-9954-20b325d35387 · outbound

This paper cites WavBERT: Exploiting Semantic and Non-Semantic Speech Us- ing Wav2vec and BERT for Dementia Detection,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning WavBERT: Exploiting Semantic and Non-Semantic Speech Us- ing Wav2vec and BERT for Dementia Detection,

Reference 20

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Observation c199ced6-0f4b-4785-b7a9-e344aa07d95c · outbound

This paper cites Alzheimer Disease Recognition Using Speech-Based Embeddings From Pre-Trained Models,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Alzheimer Disease Recognition Using Speech-Based Embeddings From Pre-Trained Models,

Reference 21

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Observation acd6cd8c-7ecc-483c-8c67-2bdcbecfe89c · outbound

This paper cites Robust speech recognition via large-scale weak supervision,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Robust speech recognition via large-scale weak supervision,

Reference 22

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Observation 4513d512-100e-4432-be63-588286661898 · outbound

This paper cites mhubert-147: A compact multilingual hubert model,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning mhubert-147: A compact multilingual hubert model,

Reference 23

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Observation 6acb5b5c-0f3f-4f92-8a59-6a609fff8eed · outbound

This paper cites Speechcare: dynamic multimodal modeling for cognitive screening in diverse linguistic and speech task contexts,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Speechcare: dynamic multimodal modeling for cognitive screening in diverse linguistic and speech task contexts,

Reference 24

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Observation e6747bb3-9b74-4255-8bc7-d2000f0600ac · outbound

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

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning wav2vec 2.0: A framework for self-supervised learning of speech repre- sentations,

Reference 25

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Observation eed1a480-169b-49c1-a220-c7dd24e6103b · outbound

This paper cites Scaling speech technology to 1,000+ languages,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Scaling speech technology to 1,000+ languages,

Reference 26

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Observation e8f6c820-69e7-4355-bd86-60dc79bc5439 · outbound

This paper cites XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale,

Reference 27

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Observation c812b28e-edf2-4cb1-ab8e-eb6bb90c7835 · outbound

This paper cites Bert: Pre- training of deep bidirectional transformers for language under- standing,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Bert: Pre- training of deep bidirectional transformers for language under- standing,

Reference 28

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Observation afcb2ad0-17fc-49e8-9343-109a27232600 · outbound

This paper cites Unsupervised cross-lingual representation learning for speech recognition,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Unsupervised cross-lingual representation learning for speech recognition,

Reference 29

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Observation f7b085e0-2aec-4e44-93fa-fe88f16c9a73 · outbound

This paper cites Multilingual E5 Text Embeddings: A Technical Report.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Multilingual E5 Text Embeddings: A Technical Report

Reference 30

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Observation 06bbf397-d7ce-4915-971f-e20100bcc798 · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-07-03T18:38:50.045645Z

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Observation ceae37e7-9693-4529-9b8d-2391c69da0bb · outbound

This paper cites The natural history of alzheimer’s disease: description of study cohort and accuracy of diagnosis,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning The natural history of alzheimer’s disease: description of study cohort and accuracy of diagnosis,

Reference 32

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Observation bd1231ae-77a6-4af4-a0ed-7ce7b7980d39 · outbound

This paper cites Discriminating speech traits of alzheimer’s disease assessed through a corpus of reading task for spanish language,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Discriminating speech traits of alzheimer’s disease assessed through a corpus of reading task for spanish language,

Reference 33

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Observation 853a1cea-77cb-4db6-9528-57a50acd7860 · outbound

This paper cites AD2021: Alzheimer’s Disease Recognition Evaluation 2021,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning AD2021: Alzheimer’s Disease Recognition Evaluation 2021,

Reference 34

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Observation 15731421-f388-4052-ab74-6502b0d14b9f · outbound

This paper cites The Dem@Care Experiments and Datasets: a Technical Report.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning The Dem@Care Experiments and Datasets: a Technical Report

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-07-03T18:38:50.052883Z

Source-reported events for the cited work

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Observation 42a0371b-d97a-4ad4-aef8-73fd42025a1c · outbound

This paper cites SUPERB: Speech Processing Universal PER- formance Benchmark,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning SUPERB: Speech Processing Universal PER- formance Benchmark,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-27T02:26:24.653249Z

Source-reported events for the cited work

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Observation 5b24c62e-146a-4a8e-aeb3-878a35dff488 · outbound

This paper cites Whisper-based transfer learning for alzheimer disease classification: Leveraging speech segments with full transcripts as prompts,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Whisper-based transfer learning for alzheimer disease classification: Leveraging speech segments with full transcripts as prompts,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-27T02:26:24.653249Z

Source-reported events for the cited work

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Observation 7727a287-3ecc-487f-8fb6-6b3f3a6ab078 · outbound

This paper cites Whisper-Based Multilin- gual Alzheimer’s Disease Detection and Improvements for Low- Resource Language,.

Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language-Invariant Multimodal Bi-Geometric Adversarial Learning Whisper-Based Multilin- gual Alzheimer’s Disease Detection and Improvements for Low- Resource Language,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-27T02:26:24.653249Z

Source-reported events for the cited work

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Pith citing papers

Observation 038342b3-2287-4c35-87ec-e3e88259c053 · inbound