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Paper Citation Record · LEDGER

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition

As of 12 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 1 inbound Pith citation observation for arXiv:2506.04652.

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

pith.paper-citation-record.v1
2506.04652 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:42:26.787485Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-13T01:04:54.506749Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T01:07:00.283281Z

Reference resolution

56 of 56 outbound references displayed

  • verified exact0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6df9723e-c5e6-4583-8a94-e73fbf8a0f6f · outbound

This paper cites Geneva: World Health Organization, 2021.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Geneva: World Health Organization, 2021

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 9a19cd28-95a6-479f-a81d-2b3ab2a73237 · outbound

This paper cites Automatic Speech Emotion Recognition Using Machine Learning,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Automatic Speech Emotion Recognition Using Machine Learning,

Reference 2

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation c60e58db-cc39-40c7-a8f4-db86e90e70b7 · outbound

This paper cites Speech Emotion Recognition using Supervised Deep Recurrent System for Mental Health Monitoring,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Speech Emotion Recognition using Supervised Deep Recurrent System for Mental Health Monitoring,

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 9ec71933-998f-4113-9bf2-6c8bb5191fc7 · outbound

This paper cites Emotion V ariation Detection in Discrete English Speech: A Wavelet Transform Use Case in Mental Health Monito ring,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Emotion V ariation Detection in Discrete English Speech: A Wavelet Transform Use Case in Mental Health Monito ring,

Reference 4

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.640598Z digest=sha256:92f5154e0cb9d1a65f9d942b786cad35709ca06abb917a9d49f87bc5fbeef123

Observation 91d7df54-7e36-4959-b229-d856d1009aad · outbound

This paper cites Emo-bias: A Large Scale Evaluation of Social Bias on Speech Emotion Recognition,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Emo-bias: A Large Scale Evaluation of Social Bias on Speech Emotion Recognition,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.264460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.643968Z digest=sha256:b504b5eab42866df6610e59ba0ee3732ea555e9069e9ead9c01f51bcf1b94dc8

Observation d37e9a31-8c4c-4ae1-924f-2811dd6c2dd2 · outbound

This paper cites Gender De-Biasing in Speech Emotion Recognition,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Gender De-Biasing in Speech Emotion Recognition,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.254770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.647021Z digest=sha256:ad9da593f6293df44814bc1b6f027d9b8d9bd7c565661c9a178e6bba07e94f1a

Observation 3d8f8907-4968-41a8-bf0f-c1a327075794 · outbound

This paper cites On the social bias of speech self-supervised models,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition On the social bias of speech self-supervised models,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.245351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.650256Z digest=sha256:495790165081c3a428557705bddeb99f5030174e13c50b570a28593a8fb90f46

Observation 45608cc5-ae52-4aff-bc41-321821ffa495 · outbound

This paper cites Mitigating subgrou p dispari- ties in multi-label speech emotion recognition: A pseudo-l abeling and unsupervised learning approach,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Mitigating subgrou p dispari- ties in multi-label speech emotion recognition: A pseudo-l abeling and unsupervised learning approach,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.236208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation e3091083-f32b-41ff-b417-431661cd22c5 · outbound

This paper cites Explor- ing data augmentation in bias mitigation against non-nativ e-accented speech,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Explor- ing data augmentation in bias mitigation against non-nativ e-accented speech,

Reference 9

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 43f57d02-b4c4-4921-a9ec-b3d60ba27209 · outbound

This paper cites Towards comprehensive subgroup performance a nalysis in speech models,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Towards comprehensive subgroup performance a nalysis in speech models,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.217396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.658985Z digest=sha256:043252394bf3f837974a94e3d000eab95e7d14336c82519894919075703e0a9a

Observation c160d415-8003-4045-9d9d-fe7488befae0 · outbound

This paper cites User-Level Differe ntial Privacy against Attribute Inference Attack of Speech Emotion Recog nition on Federated Learning,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition User-Level Differe ntial Privacy against Attribute Inference Attack of Speech Emotion Recog nition on Federated Learning,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.208070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.661768Z digest=sha256:6c159c961ab193b730bf546f22a83679c219acefc332ce5eed732ede0fedcc9f

Observation e43c49dc-5e80-43c7-8298-d06528b78194 · outbound

This paper cites Achieving Fair Speech Emoti on Recogni- tion via Perceptual Fairness,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Achieving Fair Speech Emoti on Recogni- tion via Perceptual Fairness,

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.664587Z digest=sha256:3ff81fe8e495e4ae2964b80a741de9f0e02bcf7bbf78f685590258cc4c0020a2

Observation c1e2a110-2f58-4047-aab2-ae7ef85804fe · outbound

This paper cites Balancing S peaker-Rater Fairness for Gender-Neutral Speech Emotion Recognition,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Balancing S peaker-Rater Fairness for Gender-Neutral Speech Emotion Recognition,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.188702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.667444Z digest=sha256:a0143f27d5a227a22ad18dd99e7fd4dccdebbf94abb165130380ee2f743d4abc

Observation 63cef6cb-52ca-4481-8232-4fc45ea17e67 · outbound

This paper cites Is It Still F air? Investi- gating Gender Fairness in Cross-Corpus Speech Emotion Reco gnition,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Is It Still F air? Investi- gating Gender Fairness in Cross-Corpus Speech Emotion Reco gnition,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.179134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.670040Z digest=sha256:80fcf605d3793de21ffe4e2b8438d2229fdd93992523e9d5d64ef0090f8258a1

Observation b2e0514d-3e97-4788-a447-0fe9311616cb · outbound

This paper cites Exploiting Co-occ urrence Frequency of Emotions in Perceptual Evaluations To Train A S peech Emotion Classifier,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Exploiting Co-occ urrence Frequency of Emotions in Perceptual Evaluations To Train A S peech Emotion Classifier,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.169214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 9717f03a-f3a6-4f01-b70f-8f5fd9211411 · outbound

This paper cites Open-Emotion: A Reproducible EMO-Superb For Speech Emotion Recognition Systems,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Open-Emotion: A Reproducible EMO-Superb For Speech Emotion Recognition Systems,

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation cd17f1a4-f073-4dc4-89a8-e609387d66db · outbound

This paper cites Building Naturalistic Emotion ally Balanced Speech Corpus by Retrieving Emotional Speech from Existing Podcast Recordings,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Building Naturalistic Emotion ally Balanced Speech Corpus by Retrieving Emotional Speech from Existing Podcast Recordings,

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.678460Z digest=sha256:4ae29da1c79e2d693d9fea2f26faff47855a4c3e072b773a7d99613b2dde3535

Observation 7a007c73-5478-4492-a03b-446d44d94508 · outbound

This paper cites CREMA-D: Crowd-Sourced Emotional Multimodal Ac tors Dataset,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition CREMA-D: Crowd-Sourced Emotional Multimodal Ac tors Dataset,

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation c91beacc-a161-4aea-adab-1bc33bcd4f0d · outbound

This paper cites Emotion R ecognition Systems Must Embrace Ambiguity,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Emotion R ecognition Systems Must Embrace Ambiguity,

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.683914Z digest=sha256:c28c1fc9d29a4944b90f9216c78666426fde3da8640cd6ea408ece5e82eb0ea3

Observation 4f97ed70-362d-419f-9423-19ce562be782 · outbound

This paper cites Embracing Ambiguity And Subjectivity Using The All-Inclusive Aggregation Rule For Evaluating Multi-L abel Speech Emotion Recognition Systems,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Embracing Ambiguity And Subjectivity Using The All-Inclusive Aggregation Rule For Evaluating Multi-L abel Speech Emotion Recognition Systems,

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 1d49e829-d65d-4c73-b131-015d0c90d99e · outbound

This paper cites Multi-Label Emotion Recognition of Korean Speech Data Using Deep Fusion Models,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Multi-Label Emotion Recognition of Korean Speech Data Using Deep Fusion Models,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.117722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.689551Z digest=sha256:1354f353559ddf693ff4843cc5b4d3cbaec04886eb024e0bcba67bc1fd1d1d91

Observation f3e688c6-e69f-4ce7-854e-6e11cb7c8bd1 · outbound

This paper cites Self-report captures 27 dis tinct categories of emotion bridged by continuous gradients,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Self-report captures 27 dis tinct categories of emotion bridged by continuous gradients,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.109817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.692196Z digest=sha256:c7282eb3efde56f281ba344016ed66d40d3fd04df8bbe2bac1ef4e269e545c94

Observation abc36370-d1fd-4aa6-be16-eb78e1c6cb59 · outbound

This paper cites Semantic Space Theory: A Computational Approach t o Emotion,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Semantic Space Theory: A Computational Approach t o Emotion,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.101726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.694783Z digest=sha256:223678b2c89bdbf198eadd64fdd0b905fc65cf4199b22d973f97cdfe876f3e2b

Observation 72b6b2ac-8a6c-4bae-88b0-8acfc0cb3f82 · outbound

This paper cites An Int er-Speaker Fairness-Aware Speech Emotion Regression Framework,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition An Int er-Speaker Fairness-Aware Speech Emotion Regression Framework,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.093863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.697484Z digest=sha256:9ade596385390cb07972e8bfcde83831b661927280d9e577fc6e73cb464656ed

Observation 9b042bff-b960-45bd-8421-9b24065b2ce0 · outbound

This paper cites Emo-superb: An in-depth look at sp eech emotion recognition,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Emo-superb: An in-depth look at sp eech emotion recognition,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.085333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.700213Z digest=sha256:612d1ab7368c376c8c3634c177884e1e9bbcd5482f5ed9f029248d642af0bea4

Observation 769bde29-0e9a-4471-a31e-c33d8008c5d8 · outbound

This paper cites A tiny whisper-ser: Unifying automatic sp eech recognition and multi-label speech emotion recognition tasks,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition A tiny whisper-ser: Unifying automatic sp eech recognition and multi-label speech emotion recognition tasks,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.077267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.702953Z digest=sha256:8a133512af606fdd91a8f2ea261f853d7fcb4f89fa9e2107d37b20ec9adbf9d9

Observation d9757a4d-f565-4821-b109-e98aa3aa4074 · outbound

This paper cites Stimulus Modality Mat ters: Impact of Perceptual Evaluations from Different Modalities on Spe ech Emo- tion Recognition System Performance,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Stimulus Modality Mat ters: Impact of Perceptual Evaluations from Different Modalities on Spe ech Emo- tion Recognition System Performance,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.069085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.705654Z digest=sha256:bc8305ca14f20d2e7c747855cee8089c40d59daa0dfae269ee7dc1dfec4aa14a

Observation 6c155684-3f78-4726-a09c-90c29c41e0db · outbound

This paper cites No Sampl e Left Behind: Towards a Comprehensive Evaluation of Speech Emotion Recog nition Systems,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition No Sampl e Left Behind: Towards a Comprehensive Evaluation of Speech Emotion Recog nition Systems,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.060014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.708398Z digest=sha256:9452e88d641a1ef1664f1642a1ca51ee09516804cf024ddc6792adc3976f5528

Observation 8bdf97a7-8496-4ab2-aed2-ed914d118c56 · outbound

This paper cites Minority Views Matter: Evaluating Speech Emo tion Classifiers with Human Subjective Annotations by an All-Inc lusive Aggregation Rule,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Minority Views Matter: Evaluating Speech Emo tion Classifiers with Human Subjective Annotations by an All-Inc lusive Aggregation Rule,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.051587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.711682Z digest=sha256:b7e62497b26fa4f715dea7a6844c4be68a05e88de42739e2227ad672d8a6e90e

Observation 5d290b4d-7f30-43d1-87a3-77eb19808c9d · outbound

This paper cites Common voice : A massively-multilingual speech corpus,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Common voice : A massively-multilingual speech corpus,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.043009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.714630Z digest=sha256:3e5ee78518421aed9f31f25d694754b8c7e068ef5446f72aef233afebae69ab0

Observation 5c23798e-d03e-417f-a92b-b08f8851ff53 · outbound

This paper cites Darpa timit acoustic-phonetic continous speech corpus cd-rom. nist speech disc 1-1.1,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Darpa timit acoustic-phonetic continous speech corpus cd-rom. nist speech disc 1-1.1,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.034392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.717486Z digest=sha256:18a06fd44dbbef1789ef32a8d7154c27bc078de012a5fa33e64a59ca7c2f9906

Observation 8bd1ab8c-f625-4406-9107-67483930b454 · outbound

This paper cites A Large-Scale Evaluation of Speech Foundation Models,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition A Large-Scale Evaluation of Speech Foundation Models,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.026059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.720327Z digest=sha256:af08f0d44b8f611dcfca311768f18022f6642c8022f840451941abdd10acc544

Observation aada9958-8380-40cb-b5c9-e120742516ba · outbound

This paper cites Decoupled Weight Decay Re gularization,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Decoupled Weight Decay Re gularization,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.017570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.723070Z digest=sha256:6a3af580b8a4cf9db6dcdcea0a2c38b13204ec370623205ec1b2f618444f0e52

Observation 87cdace8-4b3e-4426-a30e-da9b60a3f0a5 · outbound

This paper cites Msp-podcast ser c hallenge 2024: L’antenne du ventoux multimodal self-supervised lea rning for speech emotion recognition,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Msp-podcast ser c hallenge 2024: L’antenne du ventoux multimodal self-supervised lea rning for speech emotion recognition,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.009849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.725733Z digest=sha256:e9c3933907bf4482ae49cc6faddaf548c389e5f3e51290aaaf63cd83f3b5e844

Observation 255adc6f-39fc-406a-a2f9-d93dc78e014d · outbound

This paper cites Improv ing speech emotion recognition in under-resourced languages via spee ch-to-speech translation with bootstrapping data selection,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Improv ing speech emotion recognition in under-resourced languages via spee ch-to-speech translation with bootstrapping data selection,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:27.001844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.728488Z digest=sha256:99af18711e8b19c1ff1b024c4ff9417186215fa801b74a74109f191bbd75f4ef

Observation e9c45155-672f-438f-96c6-e2ab1dc83730 · outbound

This paper cites Equality of Opportunity in Supervised Learning,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Equality of Opportunity in Supervised Learning,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.993355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.731288Z digest=sha256:0e01f3f662d342d47b130de7153d50fe561345577a7ca01ffa6fec5276c89a10

Observation 1557e210-09f6-49c2-9ad7-97e90e003eda · outbound

This paper cites Diverse Adversaries fo r Mitigating Bias in Training,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Diverse Adversaries fo r Mitigating Bias in Training,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.985144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.734186Z digest=sha256:08b0f05d800bc4b8d352521c4e26f68baf8835f374f379a9513513257ac9819b

Observation 733ad251-af17-4a63-b60d-7ebf023e9324 · outbound

This paper cites Who gets the benefit of the doubt? racial bias in machine learning algorithms applied to secondary school math education,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Who gets the benefit of the doubt? racial bias in machine learning algorithms applied to secondary school math education,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.977110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.736892Z digest=sha256:ead95d66a0bbacfa2da5d7cee7f694ada6f2e1f068e3f340615887c83898404b

Observation cf37d029-a355-4821-b4c8-c64c8ebccf35 · outbound

This paper cites Soft-prompt tuning for large language models to evaluate bias,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Soft-prompt tuning for large language models to evaluate bias,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.968944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.739570Z digest=sha256:02a86e2585232c07f5cc9b63d2efee3e5451281735a74d60ab3dbada671d3d5d

Observation e6664579-730a-4490-9081-e1b2c9fa0c4f · outbound

This paper cites Debiasing with Su fficient Pro- jection: A General Theoretical Framework for V ector Repres entations,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Debiasing with Su fficient Pro- jection: A General Theoretical Framework for V ector Repres entations,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.960635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.742264Z digest=sha256:91391bba97820c5a259885e27bdddb26c60ac9ad178c262d2612fcd64731dfea

Observation fc61a35f-9153-4de3-82dd-4d72d4af5b94 · outbound

This paper cites Clas s-Balanced Loss Based on Effective Number of Samples,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Clas s-Balanced Loss Based on Effective Number of Samples,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.952426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.744986Z digest=sha256:c7c8d48df3c83479a33b09589028b05e8c992f2c1afdc1bca0ca18912b07f34c

Observation 7bd118d0-6f03-4466-b4d7-563f18d25fd1 · outbound

This paper cites Towards robust and privacy-preserving text representat ions,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Towards robust and privacy-preserving text representat ions,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.944514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.747724Z digest=sha256:e4e7b985b44ff3e3a5a1807ac024bb28fa291dd1808976fa6a62d9ac44a96134

Observation eb6abfa3-4343-44f6-8e6c-b5c7b2f8b4c2 · outbound

This paper cites Adversarial Removal of Demo graphic Attributes from Text Data,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Adversarial Removal of Demo graphic Attributes from Text Data,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.936480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.750389Z digest=sha256:e17dd30e75da2e1f382ab34d58abd077e4548035e7b23d9a3e96b17ab056d29c

Observation fc6a02e6-c349-4733-a8ad-29ca25e42e00 · outbound

This paper cites Diverse adversaries fo r mitigating bias in training,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Diverse adversaries fo r mitigating bias in training,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.928492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.753205Z digest=sha256:1102c6c397f878a7a052b3a1863b098e922cbf8b184e6d294d58751cb3a9ccb3

Observation 2d01bf34-7658-4e1c-bf9f-dc0f7322bceb · outbound

This paper cites Data preprocessing techniq ues for classi- fication without discrimination,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Data preprocessing techniq ues for classi- fication without discrimination,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.920581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.756094Z digest=sha256:a1b05c5cdfecee21cb292d527ef76b3186213e8a4c5a2e911ad36a2cdc00ec19

Observation 24cf42d5-7fab-4797-ad9f-ea75ceee66e7 · outbound

This paper cites BLIND: Bias removal with no de mograph- ics,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition BLIND: Bias removal with no de mograph- ics,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.912053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.759020Z digest=sha256:fe8a65538ba7e28ebf8470ede6baf032067de78a74230ae1a8f2470d2006d5bb

Observation d045a6a0-0002-4aad-905d-48287eeedf84 · outbound

This paper cites Robust Solutions of Optimization Problems Affected by Uncertain Probabilities,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Robust Solutions of Optimization Problems Affected by Uncertain Probabilities,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.902898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.761778Z digest=sha256:e56a57a124d25ff43751a59187854682b4484db8ea81b81a4e21131d7c5ebfbe

Observation ba9ac7df-1ee2-4e98-a225-24d479406ed3 · outbound

This paper cites Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generaliza- tion.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generaliza- tion

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.893075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.764588Z digest=sha256:45dde81fbe6ec990c765ff1f176dde46dc3a59abffddd8922b990424b3697d81

Observation e89cfbf3-cd4f-45f2-b99d-7ea015418879 · outbound

This paper cites Learning from failure: training debiased classifier from biased classifier,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Learning from failure: training debiased classifier from biased classifier,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.883448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.767477Z digest=sha256:f35516536b7b89dfa8b4232c25c7b1291e60c28bba4344e92c6932c6000300bb

Observation c9cb2e31-3a71-4eae-9c00-f98acff01215 · outbound

This paper cites Signal Is Harder To Learn Than Bias: Debiasing with Focal Loss,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Signal Is Harder To Learn Than Bias: Debiasing with Focal Loss,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.873899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.770189Z digest=sha256:92cbc17757c5265f111ab24b8c3fb8fb62201bd0cf372897856cebbff75efb0a

Observation 21c05440-201b-4b1e-a225-75739012dce0 · outbound

This paper cites Learning Debiased Representation via Disentangled Feature Augmentation,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Learning Debiased Representation via Disentangled Feature Augmentation,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.864643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.772932Z digest=sha256:cf884c639a8dc4a57d15e210701f71b4734759fd8b30dd045f3d007f85997bb8

Observation 4a7c4c35-49a7-4138-a627-fdb8ace8ae6a · outbound

This paper cites Unlabeled Debiasing in Downstream Tasks via Class-wise Low V ariance Regularization,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Unlabeled Debiasing in Downstream Tasks via Class-wise Low V ariance Regularization,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.855738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.775727Z digest=sha256:09a72bd7f79ceb5e3ae8e845c8306768f857249977cd683e89e171d654dfc97a

Observation 43425b44-c823-479a-9261-46a7d5fac79f · outbound

This paper cites Generalized Cross Entropy Los s for Training Deep Neural Networks with Noisy Labels,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Generalized Cross Entropy Los s for Training Deep Neural Networks with Noisy Labels,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.847124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.778668Z digest=sha256:e70a21f517f66dccfe3e986f08d11c33a9e6a84b51bece5248ec05dda77867b9

Observation fac5211a-52f4-4595-a08f-e765b31938e1 · outbound

This paper cites Beyond the binary: Li mitations and possibilities of gender-related speech technology res earch,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Beyond the binary: Li mitations and possibilities of gender-related speech technology res earch,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.839036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.781594Z digest=sha256:09e7e598ae712455fb76f581f2d5960aa5416ae853f45c2f9c363b2d86a94a07

Observation 25762776-ddf9-45c0-9dd6-1ba7713501ac · outbound

This paper cites Listen and speak fairly: a study on semantic gender bias in speech integrated large language models,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Listen and speak fairly: a study on semantic gender bias in speech integrated large language models,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.829502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.784432Z digest=sha256:7defeb9e00c1d4b11e255114afe4b70c0e7618c671b55d7e4e0540c6dceb1881

Observation b5367587-0052-4f3a-81d5-dfcb71ec4b04 · outbound

This paper cites Spoken stereoset: on evaluating social bias towar d speaker in speech large language models,.

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition Spoken stereoset: on evaluating social bias towar d speaker in speech large language models,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:42:26.819033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:42:26.787485Z digest=sha256:3de78ec0ee64bdd677a20062a6cabc439abab98b2dbd9fc24782a2248b2fb354

Pith citing papers

Observation 8f48ab17-ff27-423b-89db-412797a64c46 · inbound

AffectCodec: Emotion-Preserving Neural Speech Codec for Expressive Speech Modeling cites this paper.

AffectCodec: Emotion-Preserving Neural Speech Codec for Expressive Speech Modeling EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition

Reference 88

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:07:00.284739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-13T01:04:54.506749Z digest=sha256:1966b8cee74d2b65da013b2ff9bf40d733524e85989eb14706ba1ca915f528ef