Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-26T22:02:22.551551Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2606.18571.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-26T22:02:22.551551Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-26T22:02:22.551551Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-03T23:39:03.309059Z
54 of 54 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation e1455807-24df-4450-a113-e287c70dd89e · outbound
Fair Cognitive Impairment Detection Through Unlearning Unresolved cited work
Reference 1
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Observation cdb2c5a4-a60c-4527-89f5-a98cf3b37335 · outbound
Fair Cognitive Impairment Detection Through Unlearning Fair Cognitive Impairment Detection Through Unlearning
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Observation 55976e06-c132-43a6-9cb9-4b4baac92155 · outbound
Fair Cognitive Impairment Detection Through Unlearning unlearning
Reference 3
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Observation 11d0fa4f-d345-41db-b858-fb9c6e278e78 · outbound
Fair Cognitive Impairment Detection Through Unlearning Datasets We use the following two datasets for our experiments
Reference 4
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Observation 820033cf-94c4-4aff-8b7e-bbf2a5101de6 · outbound
Fair Cognitive Impairment Detection Through Unlearning - CM” and “-UL
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Observation b2ec2b71-de9d-4dda-844e-08af4f840b93 · outbound
Fair Cognitive Impairment Detection Through Unlearning Unresolved cited work
Reference 6
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Observation 6498bf79-e234-4aba-9f10-2d0a34ffc529 · outbound
Fair Cognitive Impairment Detection Through Unlearning All technical content, analyses, and conclusions were produced by the authors and verified for accuracy
Reference 7
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Observation f49e766c-f430-4466-98a7-eb9b60d90ae1 · outbound
Fair Cognitive Impairment Detection Through Unlearning Artifi- cial intelligence, speech, and language processing approaches to monitoring alzheimer’s disease: a systematic review,
Reference 8
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Observation 693e6e11-1df5-4ce4-a5da-6b5babec84b3 · outbound
Fair Cognitive Impairment Detection Through Unlearning Detecting Cognitive Decline Using Speech Only: The ADReSSo Challenge,
Reference 9
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Fair Cognitive Impairment Detection Through Unlearning CogniV oice: Multi- modal and Multilingual Fusion Networks for Mild Cognitive Im- pairment Assessment from Spontaneous Speech,
Reference 10
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Observation 2f2d23c3-2723-414b-a832-ebd1fc6aee48 · outbound
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Reference 11
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Observation e8a1b877-1c8c-43c3-b299-59291577d775 · outbound
Fair Cognitive Impairment Detection Through Unlearning Bias and fairness in self-supervised acoustic representations for cognitive impairment detection,
Reference 12
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Observation c4289e87-ad5d-425a-941c-fdc716188d52 · outbound
Fair Cognitive Impairment Detection Through Unlearning Don‘t take the easy way out: Ensemble based methods for avoiding known dataset biases,
Reference 13
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Observation 09f4df20-c60a-42f2-b2ff-876a9185004d · outbound
Fair Cognitive Impairment Detection Through Unlearning End- to-end bias mitigation by modelling biases in corpora,
Reference 14
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Observation a362a310-0dc7-499b-b0a0-6eb30be1da0f · outbound
Fair Cognitive Impairment Detection Through Unlearning Guide the learner: Controlling product of experts debiasing method based on token attribution similarities,
Reference 15
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Observation 26e56c33-b382-4ba3-a1c8-dc7bd90b5a9c · outbound
Fair Cognitive Impairment Detection Through Unlearning Towards debiasing NLU models from unknown biases,
Reference 16
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Observation 155d67b0-9f19-4fc9-bac0-eee3b5939870 · outbound
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Reference 17
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Observation 924bd6f1-6590-4d3e-8d1d-adc0bb5e85f1 · outbound
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Reference 18
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Observation 87f5a3f8-4238-44e0-8425-ac09d4b6b222 · outbound
Fair Cognitive Impairment Detection Through Unlearning Kernel-whitening: Overcome dataset bias with isotropic sentence embedding,
Reference 19
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Observation f4fc249e-5cd2-486d-bf8a-a398c8efde45 · outbound
Fair Cognitive Impairment Detection Through Unlearning Towards stable natural language understanding via information entropy guided debiasing,
Reference 20
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Observation 32d972dd-4de2-4c5f-997f-ffc6b7e1f4b3 · outbound
Fair Cognitive Impairment Detection Through Unlearning Robust natural language understanding with residual attention debiasing,
Reference 21
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Observation ae18c1f6-dabe-4f78-a45b-aceb01dee144 · outbound
Fair Cognitive Impairment Detection Through Unlearning Debiasing masks: A new framework for shortcut mitigation in NLU,
Reference 22
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Observation db49a75d-f3a6-4132-9950-d15fa335995c · outbound
Fair Cognitive Impairment Detection Through Unlearning FairFlow: Mitigating dataset biases through undecided learning for natural language understanding,
Reference 23
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Observation c06decf8-a71a-4554-9cbd-609b2b360d2f · outbound
Fair Cognitive Impairment Detection Through Unlearning Connected Speech-Based Cognitive Assessment in Chinese and English
Reference 24
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Observation 7a03a27b-c453-410c-80f5-c9707efe3e1c · outbound
Fair Cognitive Impairment Detection Through Unlearning Prepare: Pioneering research for early prediction of alzheimer’s and related dementias eureka challenge,
Reference 25
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Observation 271f833e-ee7e-472a-85bc-736e0153c12b · outbound
Fair Cognitive Impairment Detection Through Unlearning Linguistic features extracted by GPT-4 improve Alzheimer‘s disease detection based on spontaneous speech,
Reference 26
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Observation 197e77f0-8af7-41a8-8bd3-890ab40e3504 · outbound
Fair Cognitive Impairment Detection Through Unlearning A digital language coherence marker for monitoring dementia,
Reference 27
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Observation 00e1e3c0-7655-41ef-8b53-c618d1fc1943 · outbound
Fair Cognitive Impairment Detection Through Unlearning Reformulating NLP tasks to capture longitudinal manifestation of language disorders in people with dementia
Reference 28
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Observation 184c7a2c-6077-4fc4-8248-6b0c0322dca6 · outbound
Fair Cognitive Impairment Detection Through Unlearning Two directions for clinical data generation with large language models: Data-to-label and label-to-data,
Reference 29
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Observation 692de962-b12a-49d3-8673-2ca8b1e7e63d · outbound
Fair Cognitive Impairment Detection Through Unlearning CDA: A contrastive data augmentation method for Alzheimer‘s disease detection,
Reference 30
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Observation 3a22cf05-c743-4f40-84c3-8bcecb66fc6c · outbound
Fair Cognitive Impairment Detection Through Unlearning Domain adaptation via prompt learning for Alzheimer‘s detection,
Reference 31
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Fair Cognitive Impairment Detection Through Unlearning Introduction to large language models (llms) for dementia care and research,
Reference 32
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Observation 8077f0e6-a2f1-4bd7-990d-932396f7c39a · outbound
Fair Cognitive Impairment Detection Through Unlearning On the social bias of speech self-supervised models,
Reference 33
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Observation 9a9a1f4d-b3df-4580-8968-bc07fa0a1d99 · outbound
Fair Cognitive Impairment Detection Through Unlearning Emo- bias: A large scale evaluation of social bias on speech emotion recognition,
Reference 34
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Observation 336e40de-0993-4d5b-8129-d9ed37b5c6c3 · outbound
Fair Cognitive Impairment Detection Through Unlearning Automatic classification of news subjects in broadcast news: Ap- plication to a gender bias representation analysis,
Reference 35
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Observation deb8897b-33a4-4e00-95c6-c794c05317ef · outbound
Fair Cognitive Impairment Detection Through Unlearning Exploring sources of racial bias in automatic speech recognition through the lens of rhythmic varia- tion,
Reference 36
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Observation ad8d779b-9fc8-4500-af98-9a867e1c8ce3 · outbound
Fair Cognitive Impairment Detection Through Unlearning A con- trastive learning approach to mitigate bias in speech models,
Reference 37
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Observation b4cb7281-426f-4fc3-b790-31b8723941a8 · outbound
Fair Cognitive Impairment Detection Through Unlearning Mitigating bias against non-native accents,
Reference 38
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Fair Cognitive Impairment Detection Through Unlearning Au- tomatic children speech sound disorder detection with age and speaker bias mitigation,
Reference 39
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Observation 1fb11a5e-a02e-4ea1-beac-9d18377c1c95 · outbound
Fair Cognitive Impairment Detection Through Unlearning Revealing con- founding biases: A novel benchmarking approach for aggregate- level performance metrics in health assessments,
Reference 40
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Fair Cognitive Impairment Detection Through Unlearning Unveil Multi-Picture Descriptions for Multilingual Mild Cognitive Impairment Detection via Contrastive Learning
Reference 41
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Observation c2a8727d-c8bb-4075-850d-5ecdc7b89ab8 · outbound
Fair Cognitive Impairment Detection Through Unlearning Speech Unlearning,
Reference 42
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Fair Cognitive Impairment Detection Through Unlearning Unsupervised domain adaptation by backpropagation,
Reference 43
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Observation ff6bf99a-3eb7-4fd1-bd86-191f1c9b847e · outbound
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Reference 44
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Observation 9a4df732-a144-40e3-ab20-a6fc33136377 · outbound
Fair Cognitive Impairment Detection Through Unlearning The interspeech 2024 taukadial challenge: Multilingual mild cognitive impairment detection with multimodal approach,
Reference 45
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Fair Cognitive Impairment Detection Through Unlearning Robust speech recognition via large-scale weak su- pervision,
Reference 46
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Fair Cognitive Impairment Detection Through Unlearning Unresolved cited work
Reference 47
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Fair Cognitive Impairment Detection Through Unlearning Sigmoid loss for language image pre-training,
Reference 48
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Observation 58fb5a24-b04e-4ff4-b17b-dcd27f3e4a39 · outbound
Fair Cognitive Impairment Detection Through Unlearning Last layer re-training is sufficient for robustness to spuri- ous correlations,
Reference 49
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Observation 8a1cbd94-90d1-48a1-9c0f-1a1d53de2938 · outbound
Fair Cognitive Impairment Detection Through Unlearning Change is Hard: A Closer Look at Subpopulation Shift
Reference 50
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Observation 99b61b42-d92d-4718-bd97-fd97c394cef8 · outbound
Fair Cognitive Impairment Detection Through Unlearning Do students debias like teachers? on the distillability of bias mitigation methods,
Reference 51
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Fair Cognitive Impairment Detection Through Unlearning AST: Audio Spectrogram Transformer,
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Fair Cognitive Impairment Detection Through Unlearning Unsupervised cross-lingual representation learning for speech recognition,
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Observation f53c58ae-a16c-46d4-aeff-f43ad3865b0d · outbound
Fair Cognitive Impairment Detection Through Unlearning Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
Reference 54
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Observation cdb2c5a4-a60c-4527-89f5-a98cf3b37335 · inbound
Fair Cognitive Impairment Detection Through Unlearning Fair Cognitive Impairment Detection Through Unlearning
Reference 2
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