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Paper Citation Record · LEDGER

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

As of 17 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 2026-08-17T06:30:58.91139+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=sha256:81ea4a8e888f80d2923b91c35bae19e8254588b6a37c6f1503c8ee9f503a4a05

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:23.544628Z digest=sha256:573c843b59c13a61af191d96cddec09d87668dca4825fceee3a0b7da69ea6ec2

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:23.654968Z digest=sha256:60e62ef91eda1a71e4e518fbe1d13a63eed66c241b8b36d9516383c7211e7105

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:23.773414Z digest=sha256:d4f32e59502ac5a5adf05e7bdab98e58ce3d90ed6cae3c6639acdfe1880ed94d

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:23.940640Z digest=sha256:2c8ac623fda99e01dbeade500f110b2a8a562f549cbf455ffe7e33f9ede23686

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:24.060331Z digest=sha256:b7b7c350f3596b728b1cef8aa6cd9a26cfc0aed46f5bbbba8b6095be7bbc873e

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:24.212370Z digest=sha256:5740c7bed506a5158ad77ebf0e88e89dfb4860a95fb5b1ffe942e3ac20068725

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:24.372886Z digest=sha256:b562fe7e9e00057a227b3a5138e9692f7c4a06edf5f439b348e785b97a8fc74b

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:24.504122Z digest=sha256:5ff6ce461d301aee3b5aefc9052d4323b15e284fd92b011351946c43c048fa25

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:24.618688Z digest=sha256:b10be46d3f3d3236d2a2b31d21b6e62a42164b67bd4b836862d8a5f5b5db10b8

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:24.761531Z digest=sha256:1817ddc0766896b69305370db512d953c9f70a1bfa33fd61dd43a3f9ecdaf805

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=sha256:11d52f9d96217799a6e4a8a4d9d91abe51ce941aa7a4e380621f4694f7cc0e05

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:25.006797Z digest=sha256:ec5b96169c814d8daeea3231a28f7b1894ea1cfa085c9dc7a338c607ac9761a7

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:25.117728Z digest=sha256:9311ea7734d42ab0d6bc0a639d6743ff11394775614fdb024bed904c3508655d

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:25.239183Z digest=sha256:aa583651771f1c544fc86413607f0c0e39e395d074b1f714756d25ccfc8bb10a

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:25.382377Z digest=sha256:4dfb7945440671f5287e75284522c00e01e9d34d66c8658438b395b007cf8817

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:25.514058Z digest=sha256:c8548e737d30f5e3c31c653879b22500a8237d6d2765a6814259c5d5045e9fb2

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:25.654630Z digest=sha256:57281da0c9d7d179a648f6b6cbfe693d5c9a3cf405339ed10a20d4cf215ceb1a

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:25.792885Z digest=sha256:02b2bbfd98fe80138fd648ba627352c0fcc5035bd29c0cf0312638d1d3bc3c34

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:25.914974Z digest=sha256:755ddce3074bcd45b4d6d43e26219dc0162aee59db0d02f34a85b8f75960f9b4

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:26.017141Z digest=sha256:1207c94d1b4b6e5539237a03e307ef5906d7738097bedf94e8c56ae1eb5cd626

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=sha256:28448d0a9dfca2a19800d843b9e318944515aede26a6e6f98202efeff8dc3d74

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:26.229399Z digest=sha256:c90ea4bc1877b1ff652d80d237072ff11d828818450a3bb4103cc608e0dff5f9

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:26.349187Z digest=sha256:df46eb8c0d3c9517df7a61ae4e8a9781bb0cc39a112b1b7693bad4bb1348f624

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:26.473567Z digest=sha256:8bbc89d9569814d8ea1b6cf7d18baeb13d5cad8139603d2798e8c0e4fb883e01

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:26.610321Z digest=sha256:eeaebd04fd91d8da59c2b45173edf9729192bddcb4c0cd949d38f7e7fff74895

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:26.735695Z digest=sha256:a5c899c18c02af991ec594039ac73832ad9318315c7b46e9f82017b9381d5029

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:26.875962Z digest=sha256:1db063a9efcc798a7934524e1b5c8e38db0093a5f92cb9ea9ef09f982c969144

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:26.997422Z digest=sha256:7f95adb2d6f933845a2d042526c5b598f112aa04b13c3fe74b45b284ce4c47c6

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:27.127918Z digest=sha256:27f7ac321bca5d43e68cdd5bba561e16242655464705f5e34c672c5d99ccf08a

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:d3714aba03d40be04d2bec1abdaba85f7247807b1d211b9dadf2098588526b2d

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:27.463252Z digest=sha256:34b80e3cb6ebe6b81f9461ae7bc6962c187133ac65b4ad12f9029d1578a3f3d7

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:27.585621Z digest=sha256:002f49a50bdb805f4a57f1ffc28984ae8c7345214386ea6828692ce43e4a59e1

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:27.717558Z digest=sha256:2c3f2b2f78059b840aeea48fe1294fee6bd42e9746feffd1033cdc1a97fb8b1b

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:27.832798Z digest=sha256:1e1a8ebc5ec5bc713ee3a96f92d35bddf85e1325aa9d72383afb3a6ea2489317

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:27.928192Z digest=sha256:2695b2660623b85b5f78cc99e1d9d32d541003b42ee544740a0c5fe9680c73cc

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:28.067844Z digest=sha256:e93e065a8fc7882d5c19ec4aa3899bfab73bd432b271e8c1915d0fc5329357c1

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:f38553873ba45bc4c74079d3dd7dceee208a022af7c8cda8369e662173edcfa2

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T15:09:28.386700Z digest=sha256:cbc356664a6ee572633929c64c638e66a84c7269904a7d8a6cb653b6667545d1

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=sha256:81ea4a8e888f80d2923b91c35bae19e8254588b6a37c6f1503c8ee9f503a4a05

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-08T19:11:30.638672Z digest=sha256:5d4a76d45ecdde52af840308c3e00bcd1bc05e59b3ac9bc1e340c0361cbad390

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-30T22:11:44.891731Z digest=sha256:c00d2832dffceef7ef409457ef8c9fcd357984a2404c9fe60c43c0bae6016022