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Paper Citation Record · LEDGER

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning

As of 8 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 3 inbound Pith citation observations for arXiv:2505.16220.

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

pith.paper-citation-record.v1
2505.16220 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:09:28.386700Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:09:23.482691Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

39 of 39 outbound references displayed

  • verified exact0
  • verified fuzzy32
  • unresolved6
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation ecaa7c47-827e-4368-8e54-5bfd8e07e92f · outbound

This paper cites Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T15:09:23.482691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:09:23.482691Z digest=sha256:02aed6f3249e2848689f89b9fc9001d2d64cf8ad46add11b7d5cf7b38b259576

Observation a2a68036-7bbd-4473-821a-d7598f049aea · outbound

This paper cites Backbone SER Framework We employ a unified model architecture based on the s3prl toolkit [25].

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Backbone SER Framework We employ a unified model architecture based on the s3prl toolkit [25]

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:36.225641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:23.544628Z digest=sha256:290abe5804aa03e667ece526d1a69a71a06ee2944d42562814e450d59936c3ca

Observation 7a2ab609-3a2e-4913-bfc2-a17f326fbb62 · outbound

This paper cites other.” We exclude the “other.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning other.” We exclude the “other

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:36.082426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:23.654968Z digest=sha256:31530a121f77cc4820b028a2e99d538ab682818c4ad99cd102a722b901342173

Observation a2d022cc-adec-47b1-9025-17b664acc572 · outbound

This paper cites Proposed Meta-PerSER Table 1 demonstrates that Meta-PerSER consistently outper- forms all baseline methods across both Seen and Unseen Data scenarios and across all upstream models.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Proposed Meta-PerSER Table 1 demonstrates that Meta-PerSER consistently outper- forms all baseline methods across both Seen and Unseen Data scenarios and across all upstream models

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:35.934863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:23.773414Z digest=sha256:70d184b93eeb1cf9ba31f17187cb1732f56bffe30ce180241adb64f99f368081

Observation 764b443b-6373-4165-95d3-e61cf8a04097 · outbound

This paper cites an unresolved cited work.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Unresolved cited work

Reference 5

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unresolved
raw_fallback, observed 2026-08-07T15:09:35.732571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:23.940640Z digest=sha256:1d2d1622fbaa241b53b3f805d2c8788767232a77d03edbbc2aef294ccca6d8e9

Observation 99841a1e-c773-4ab1-8d11-0581f2d683cb · outbound

This paper cites Meta-PerSER integrates a pre-trained self-supervised backbone with Combined-Set Meta- Training, Derivative Annealing, and per-layer adaptive learning rates.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Meta-PerSER integrates a pre-trained self-supervised backbone with Combined-Set Meta- Training, Derivative Annealing, and per-layer adaptive learning rates

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:35.580645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:24.060331Z digest=sha256:84769e5433c80a8f11b3658949b2edd36d6eb29da5c1704287ba8626d93b16c0

Observation 09044711-7e64-47fb-a00c-7ce5c7350f2b · outbound

This paper cites Speech emotion recognition combining acoustic features and linguistic information in a hy- brid support vector machine-belief network architecture,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Speech emotion recognition combining acoustic features and linguistic information in a hy- brid support vector machine-belief network architecture,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:35.416286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:24.212370Z digest=sha256:428d30a56a93d48250a9d4068803e16870861f0f2201399638ade0b8824c5ab9

Observation f7121961-ccf2-4346-a129-e63f11d6825f · outbound

This paper cites Speech Emotion Recognition Using Deep Learn- ing Techniques: A Review,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Speech Emotion Recognition Using Deep Learn- ing Techniques: A Review,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:35.223662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:24.372886Z digest=sha256:014b5320ea519c3fd4845551ebc8dea431545af99c874d6ffea2fd744aff6d64

Observation a15afbb7-abec-4c16-b06a-e9961507c104 · outbound

This paper cites Speech Emotion Recognition with Fusion of Acoustic- and Linguistic-Feature- Based Decisions,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Speech Emotion Recognition with Fusion of Acoustic- and Linguistic-Feature- Based Decisions,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:35.029795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:24.504122Z digest=sha256:96e9ee2906cafde2cde2844e63a1cd28ef5353d28f5dc9affcfa2f065644d4f8

Observation c7ab34d7-b9eb-49a3-86cb-c8ad2a1785d6 · outbound

This paper cites EMO-Codec: An In-Depth Look at Emotion Preservation Capacity of Legacy and Neural Codec Models with Subjective and Objective Evaluations,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning EMO-Codec: An In-Depth Look at Emotion Preservation Capacity of Legacy and Neural Codec Models with Subjective and Objective Evaluations,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:34.858958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:24.618688Z digest=sha256:7a02d42e052e5839c2f9d1d00241d80da0e99976d95be7c3c52c4c945fd0d4b3

Observation 7dc1b3bc-e465-42cf-a8d4-1385527c3c73 · outbound

This paper cites Interpreting ambiguous emotional expressions,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Interpreting ambiguous emotional expressions,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:34.699354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:24.761531Z digest=sha256:9e5457553f5238c9d67f03b802fd43157d3d78a26e55cfee050bdc650865a1b3

Observation 6a84702f-8403-4d32-a0ea-222621795bcb · outbound

This paper cites The Ambiguous World of Emotion Representation.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning The Ambiguous World of Emotion Representation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T15:09:24.902229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:09:24.902229Z digest=sha256:dd293b46fb112af333bd9174c22df1ba3f88fa8b06bd44e983391fb403497caa

Observation 47a10a85-eb28-4209-b7fc-ff148de5fd7c · outbound

This paper cites Speaker Attentive Speech Emotion Recognition,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Speaker Attentive Speech Emotion Recognition,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:34.545899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:25.006797Z digest=sha256:464271959c1b967ecbd7ac6ad2b9ec662876dd4f4b2d7f93891dec930b1b5792

Observation eeac684d-bbe6-4ffd-90fa-b59e9034574b · outbound

This paper cites Personalized Adapta- tion with Pre-trained Speech Encoders for Continuous Emotion Recognition,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Personalized Adapta- tion with Pre-trained Speech Encoders for Continuous Emotion Recognition,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:34.348824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:25.117728Z digest=sha256:c94920c16310dd51a2025c9879ab55c80884c07618fc5c1592ffc655d650a59b

Observation 612d0aa4-429b-45f9-8201-82504ff89a89 · outbound

This paper cites The “Problem.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning The “Problem

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:34.214333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:25.239183Z digest=sha256:5474ceeb794222db4aff612bdee695f9a1680a5567d5d90aabfce8bb609f34d7

Observation 37054a00-36a1-4ebf-bfc7-320c2cf313d6 · outbound

This paper cites DICES Dataset: Diversity in Conversational AI Evaluation for Safety,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning DICES Dataset: Diversity in Conversational AI Evaluation for Safety,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:34.054503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:25.382377Z digest=sha256:bc2cfe0e5b0d6f7f623a290a77f683a4f1d50ffae5717ef50d42666138d4e555

Observation 05c512d8-b149-4ba7-802b-da4e402aa0f4 · outbound

This paper cites On Re- leasing Annotator-Level Labels and Information in Datasets,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning On Re- leasing Annotator-Level Labels and Information in Datasets,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:33.857690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:25.514058Z digest=sha256:fce063d79498b5578dacd2d9fffc3543c5fef4c6f7fb02312621bce06b93127c

Observation 33ae503b-aeb8-4a90-be21-ca083732fc4f · outbound

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

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Open-Emotion: A Reproducible EMO-Superb For Speech Emotion Recognition Systems,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:33.708913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:25.654630Z digest=sha256:9a5dcf25a0b5dd85b1217907340822d751d016a79599616ebe34155404780b64

Observation ee086334-d68c-4754-b5e3-508455a77c9d · outbound

This paper cites Every Rating Matters: Joint Learn- ing of Subjective Labels and Individual Annotators for Speech Emotion Classification,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Every Rating Matters: Joint Learn- ing of Subjective Labels and Individual Annotators for Speech Emotion Classification,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:33.560933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:25.792885Z digest=sha256:edf6ef369bb13fb117d088d476043bb2330ec91420d89343e96e9201506f900e

Observation edd9bd00-aae3-4b9a-ac2b-37425e7b7116 · outbound

This paper cites Dealing with Dis- agreements: Looking Beyond the Majority V ote in Subjective Annotations,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Dealing with Dis- agreements: Looking Beyond the Majority V ote in Subjective Annotations,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:33.439858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:25.914974Z digest=sha256:cd5079fe5a03050e751385bdf17908717013565daa8e92a9fa118e6a99dcb9c5

Observation d89b476b-f03b-4402-bae4-199196b66a55 · outbound

This paper cites Meta- Learning in Neural Networks: A Survey,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Meta- Learning in Neural Networks: A Survey,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:33.160134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:26.017141Z digest=sha256:7e6fb90c885d1552d98254bdd4166a9e068e92244d1954346d3e7f1eace50b34

Observation 1075fe1d-4524-4132-bb51-d908ee6451c8 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Model-agnostic meta-learning for fast adaptation of deep networks,

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T15:09:26.124390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:09:26.124390Z digest=sha256:7cdaa515719ccc388574d9dbb5dbbe9e94ae81069bf70aeb76cf04a4f35716fe

Observation 29b61794-18d6-4812-930e-10103b51ee56 · outbound

This paper cites Optimization as a Model for Few- Shot Learning,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Optimization as a Model for Few- Shot Learning,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:32.862748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:26.229399Z digest=sha256:a9a79b877f42da380c9d6f7d994dafd8387c944eaab5f5740c7a9bca0e294ae5

Observation c5e40ac8-04bb-4e51-b545-cd0961ed4f06 · outbound

This paper cites Meta-Learning for Speech Emotion Recognition Considering Ambiguity of Emotion Labels,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Meta-Learning for Speech Emotion Recognition Considering Ambiguity of Emotion Labels,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:32.583112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:26.349187Z digest=sha256:ddbc2745f41dace0140433876aa435cd8f3261b0d6f6a6bd518a812f92d226b0

Observation cbc67106-18e7-49ba-903b-e00bafc7d770 · outbound

This paper cites Meta- Learning for Low-Resource Speech Emotion Recognition,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Meta- Learning for Low-Resource Speech Emotion Recognition,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:32.266809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:26.473567Z digest=sha256:3c2f5f456a1b61a6b68ee50e9dc03458bc4b2a3dcbfbfec330c8d2929216bfe6

Observation 8baf4a67-9bf7-4dd7-9667-7ca72a788dfa · outbound

This paper cites Dealing with Dis- agreements: Looking Beyond the Majority V ote in Subjective Annotations,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Dealing with Dis- agreements: Looking Beyond the Majority V ote in Subjective Annotations,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:32.009550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:26.610321Z digest=sha256:dc20056b123d2339328021c5a5c09dc2ec3e20da60a88540084e1d61c2f34107

Observation 31b04a2c-4be4-4134-911f-89e228f0297d · outbound

This paper cites Speech emotion recognition based on meta-transfer learning with domain adaption,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Speech emotion recognition based on meta-transfer learning with domain adaption,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:31.730538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:26.735695Z digest=sha256:c79a9453ed8e06a33b1452510d3962b196ed2cb54af540ae0b2bd486e7655579

Observation 8a12fb9a-39c1-45ec-be76-cf8199f95d97 · outbound

This paper cites On efficacy of Meta-Learning for Domain Generalization in Speech Emotion Recognition,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning On efficacy of Meta-Learning for Domain Generalization in Speech Emotion Recognition,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:31.444958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:26.875962Z digest=sha256:546082a0d4b4d657e60e0b2021c5fdcd381c486e73971499b817601f05db6699

Observation 49c444e8-b95b-426a-966e-f3b71ef5d1b8 · outbound

This paper cites Learning to Recognize Per-Rater’s Emotion Perception Using Co-Rater Training Strategy with Soft and Hard Labels,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Learning to Recognize Per-Rater’s Emotion Perception Using Co-Rater Training Strategy with Soft and Hard Labels,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:31.115676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:26.997422Z digest=sha256:f14ba7604f2f4c4c05cc0619709a9412b94bd83606ec91cf4110b64e0c3013b3

Observation 37ea7bbf-d707-4138-9b1c-172197fc2ed9 · outbound

This paper cites IEMOCAP: Interactive emotional dyadic motion capture database,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning IEMOCAP: Interactive emotional dyadic motion capture database,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:30.863409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:27.127918Z digest=sha256:fc6156e2fa17769e34549cc37e922a65394e00e10afbdd83e481f23192690042

Observation a76636bf-08d4-452d-bba5-e405d48764a8 · outbound

This paper cites SUPERB: Speech Processing Universal PERformance Benchmark,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning SUPERB: Speech Processing Universal PERformance Benchmark,

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T15:09:27.305920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:09:27.305920Z digest=sha256:be30bfb0115b000da2a5c7ad6eea416ebe1002c5d4ce20552236572902209221

Observation c30a1408-254a-448e-9e31-0e405344efd9 · outbound

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

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning wav2vec 2.0: a framework for self-supervised learning of speech representa- tions,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:30.567152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:27.463252Z digest=sha256:298381377e0625b36034fd5cad6fd60111da984cfde66afaea2bb7598acc382d

Observation a5fa9ae3-f087-42f2-8fa1-ee772ad1990a · outbound

This paper cites HuBERT: Self-Supervised Speech Rep- resentation Learning by Masked Prediction of Hidden Units,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning HuBERT: Self-Supervised Speech Rep- resentation Learning by Masked Prediction of Hidden Units,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:30.190577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:27.585621Z digest=sha256:94ca76dbe2d40a05f9f1152ca4bcaaef9ea8b5c248f8dd3a6df5d5b870ae2846

Observation 55c61b94-62fe-4784-83cb-e3a0e370e95e · outbound

This paper cites WavLM: Large-Scale Self-Supervised Pre- Training for Full Stack Speech Processing,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning WavLM: Large-Scale Self-Supervised Pre- Training for Full Stack Speech Processing,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:29.894914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:27.717558Z digest=sha256:76d30cc017690b33febd4dbdc27c2588fb63f4136296db836f922db330ea255b

Observation 0e833bb9-e452-4fad-aecc-31b3161aa58f · outbound

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

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Class- Balanced Loss Based on Effective Number of Samples,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:29.591860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:27.832798Z digest=sha256:8657122adde6a593294c2e8c05de91c96aa7f3de8036eb051dabd09fb6a3d23f

Observation 9c949f02-5630-40a6-b272-eb779f2931c6 · outbound

This paper cites How to train your MAML,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning How to train your MAML,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:29.267113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:27.928192Z digest=sha256:78404d668c3a62046a3735522b5c1a3e63ee4052fcd0e73cf47edfb5296e2564

Observation ff40ef00-877f-4d1d-a941-3cccf3aaa559 · outbound

This paper cites Few-Shot Acoustic Event Detection Via Meta Learn- ing,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Few-Shot Acoustic Event Detection Via Meta Learn- ing,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:09:28.971431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:28.067844Z digest=sha256:de2e4140bcf118db8a3dc8cfd0f4b88b9638b14b31d1775f5bf2bf7125e17589

Observation e3d2a4c4-9b03-44b0-abf8-b2b9e54f1dee · outbound

This paper cites Macro F1 and Macro F1.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Macro F1 and Macro F1

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T15:09:28.255290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:09:28.255290Z digest=sha256:2ca8774ffddd4dad95be7749082113c87e1bc0d6a196e3691c07f85cb7361268

Observation a57f0bac-014d-4f3b-8276-070188614498 · outbound

This paper cites Emo- bias: A large scale evaluation of social bias on speech emotion recognition,.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Emo- bias: A large scale evaluation of social bias on speech emotion recognition,

Reference 39

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T15:09:28.665534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:09:28.386700Z digest=sha256:1f76a88eb5c61bef6eadeacf761a3809e74c429156969a66b4eab5f2df156d54

Pith citing papers

Observation ecaa7c47-827e-4368-8e54-5bfd8e07e92f · inbound

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning cites this paper.

Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T15:09:23.482691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:09:23.482691Z digest=sha256:02aed6f3249e2848689f89b9fc9001d2d64cf8ad46add11b7d5cf7b38b259576

Observation 683bc5d7-4f13-4b73-9ec5-28c656249489 · inbound

Mixed-Precision Information Bottlenecks for On-Device Trait-State Disentanglement in Bipolar Agitation Detection cites this paper.

Mixed-Precision Information Bottlenecks for On-Device Trait-State Disentanglement in Bipolar Agitation Detection Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning

Reference 93

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:00:36.697028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-08T19:11:30.638672Z digest=sha256:c341fbb547183d98939c8283c3f3eddcef33b0f98ecfda944e99fded7ef11658

Observation 0a24cfb7-9a25-414f-8cfb-eac97702ed2c · inbound

Afrispeech Semantics: Evaluating Audio Semantic Reasoning in Spoken Language Models Across Domains and Accents cites this paper.

Afrispeech Semantics: Evaluating Audio Semantic Reasoning in Spoken Language Models Across Domains and Accents Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning

Reference 236

Resolution
verified exact
arxiv_id, observed 2026-06-30T22:15:05.601545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-30T22:11:44.891731Z digest=sha256:db006d31b3efcca0c5e5caa36a12941119aedc5b2dc728e59b4365c2412a1552