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Paper Citation Record · LEDGER

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition

As of 7 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2607.16290.

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

pith.paper-citation-record.v1
2607.16290 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T07:10:38.234748Z

measured 36 of 36 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

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External citation measurements

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Outbound references

Observation 7e4a5bca-bdc2-4611-b150-4d0ec0c36afa · outbound

This paper cites A Shared Latent for Partially-Labeled Multi-Task Facial Affect Recognition.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition A Shared Latent for Partially-Labeled Multi-Task Facial Affect Recognition

Reference 1

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Observation 6e40a4d9-de1b-41b6-bd11-76c098267ed5 · outbound

This paper cites 7th abaw competition: Multi-task learning and compound expression recognition,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition 7th abaw competition: Multi-task learning and compound expression recognition,

Reference 2

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Observation 8bcba267-1af7-4334-8b0a-9c272c44dd19 · outbound

This paper cites From affect to complex behavior: Advancing multimodal human-centered ai at the 10th abaw workshop & competition,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition From affect to complex behavior: Advancing multimodal human-centered ai at the 10th abaw workshop & competition,

Reference 3

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Observation b8317ae9-9d9d-4f2e-8085-03af2c3a1b53 · outbound

This paper cites Deep affect prediction in-the- wild: Aff-wild database and challenge, deep architectures, and beyond,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Deep affect prediction in-the- wild: Aff-wild database and challenge, deep architectures, and beyond,

Reference 4

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Observation 87c776af-f7fe-4406-b257-8776e5cf7877 · outbound

This paper cites Abaw: Valence-arousal estimation, expression recognition, action unit detection & multi-task learning challenges,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Abaw: Valence-arousal estimation, expression recognition, action unit detection & multi-task learning challenges,

Reference 5

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Observation 83679afa-258e-4851-8805-bd41b0ce5251 · outbound

This paper cites Abaw: Learning from synthetic data & multi-task learning challenges,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Abaw: Learning from synthetic data & multi-task learning challenges,

Reference 6

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Observation 03725ef2-6365-43a8-a554-323e54c9a319 · outbound

This paper cites The 6th affective behavior analysis in-the-wild (abaw) competition,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition The 6th affective behavior analysis in-the-wild (abaw) competition,

Reference 7

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Observation d7fff2c2-c909-4820-9ca3-46663a04fa84 · outbound

This paper cites Affective behavior analysis using action unit relation graph and multi- task cross attention,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Affective behavior analysis using action unit relation graph and multi- task cross attention,

Reference 8

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Observation 2d0f0048-22f6-40f0-8fef-d69973f0c76d · outbound

This paper cites Affective behavior analysis using task- adaptive and AU-assisted graph network,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Affective behavior analysis using task- adaptive and AU-assisted graph network,

Reference 9

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Observation 03c4f0ad-a332-4ece-93b7-6b7687cdbef6 · outbound

This paper cites HSEmotion Team at the 7th ABAW Challenge: Multi-Task Learning and Compound Facial Expression Recognition.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition HSEmotion Team at the 7th ABAW Challenge: Multi-Task Learning and Compound Facial Expression Recognition

Reference 10

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Observation db81d9bd-070b-4081-beba-475ef076ad02 · outbound

This paper cites Affective be- haviour analysis via progressive learning,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Affective be- haviour analysis via progressive learning,

Reference 11

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Observation 2d8e1186-63ec-4a68-bc49-d5be1e738c17 · outbound

This paper cites A multi-task mean teacher for semi-supervised facial affective behavior analysis,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition A multi-task mean teacher for semi-supervised facial affective behavior analysis,

Reference 12

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Observation 222d6547-ef99-4a5a-a0e8-fe59c569c79f · outbound

This paper cites SS- MFAR: Semi-supervised multi-task facial affect recognition,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition SS- MFAR: Semi-supervised multi-task facial affect recognition,

Reference 13

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Observation a88fa9c8-167c-4771-ae1e-39db6c3e12a2 · outbound

This paper cites Semi- supervised learning with deep generative models,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Semi- supervised learning with deep generative models,

Reference 14

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Observation 1583f1b3-3f08-4c3a-aa80-c2035f3114fe · outbound

This paper cites Neural network ensembles, cross validation, and active learning,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Neural network ensembles, cross validation, and active learning,

Reference 15

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Observation cd656eac-15de-4453-bf44-264fc44984df · outbound

This paper cites Diversity creation methods: a survey and categorisation,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Diversity creation methods: a survey and categorisation,

Reference 16

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Observation c66a0ee0-09d5-4f58-b5cc-095393bbe39c · outbound

This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Simple and scalable predictive uncertainty estimation using deep ensembles,

Reference 17

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Observation fd8a9aa2-c685-4e10-b19e-f04d74edbd61 · outbound

This paper cites LoRA: Low-rank adaptation of large language models,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition LoRA: Low-rank adaptation of large language models,

Reference 18

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Observation 389d6158-13a9-4949-a1b7-24a860e154a4 · outbound

This paper cites LoRA ensembles for large language model fine-tuning.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition LoRA ensembles for large language model fine-tuning

Reference 19

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Observation 11e51d8d-ed0c-4748-8776-7bbcf5faceb8 · outbound

This paper cites FSFM: A generalizable face security foundation model via self-supervised facial representation learning,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition FSFM: A generalizable face security foundation model via self-supervised facial representation learning,

Reference 20

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Observation c4657fe8-3884-47a6-a997-1ae78336e97a · outbound

This paper cites Multi-modal facial affective analysis based on masked autoencoder,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Multi-modal facial affective analysis based on masked autoencoder,

Reference 21

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Observation 7649b5c3-572b-4e5b-9382-70bfbf8c1db3 · outbound

This paper cites AffectNet: A database for facial expression, valence, and arousal computing in the wild,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition AffectNet: A database for facial expression, valence, and arousal computing in the wild,

Reference 22

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Observation 57acbd43-1b8b-40cd-897e-fd92e2bbf93f · outbound

This paper cites DINOv2: Learning robust visual features without supervision,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition DINOv2: Learning robust visual features without supervision,

Reference 23

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Observation 8cfd5c8d-af63-42d3-b489-61dca118d0a9 · outbound

This paper cites EmotioNet: An accurate, real-time algorithm for the automatic annotation of a million facial expressions in the wild,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition EmotioNet: An accurate, real-time algorithm for the automatic annotation of a million facial expressions in the wild,

Reference 24

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Observation a321ba72-9535-4fdb-b4cf-e84079777cc7 · outbound

This paper cites Aff-wild: Valence and arousal ‘in-the-wild’ challenge,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Aff-wild: Valence and arousal ‘in-the-wild’ challenge,

Reference 25

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Observation aafe458d-1a6a-4255-9aac-9c34ed1fa582 · outbound

This paper cites Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace

Reference 26

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Observation 028506a2-b1dd-4d1e-ae2d-f963e8884da7 · outbound

This paper cites Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network

Reference 27

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Observation 02700bd3-8e2f-479d-b6df-ec88955b6663 · outbound

This paper cites Analysing affective behavior in the first abaw 2020 competition,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Analysing affective behavior in the first abaw 2020 competition,

Reference 28

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Observation b123bf43-ffdf-4e82-abbb-d0c046c570cc · outbound

This paper cites Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework

Reference 29

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Observation e42deeb0-b18d-41dd-8460-518d191640a5 · outbound

This paper cites Analysing affective behavior in the second abaw2 competition,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Analysing affective behavior in the second abaw2 competition,

Reference 30

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Observation 4fc027e4-1b8f-45b1-89ca-5bdcfa9c4699 · outbound

This paper cites Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study

Reference 31

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Observation 1aac84a9-384c-4e8f-bb05-56529f029f51 · outbound

This paper cites Abaw: Valence-arousal estimation, expression recognition, action unit detection & emotional reaction intensity estimation challenges,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Abaw: Valence-arousal estimation, expression recognition, action unit detection & emotional reaction intensity estimation challenges,

Reference 32

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Observation bf67626f-4d95-47ca-8c6e-5e07403105f8 · outbound

This paper cites Distribution matching for multi-task learning of classification tasks: a large-scale study on faces & beyond,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Distribution matching for multi-task learning of classification tasks: a large-scale study on faces & beyond,

Reference 33

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Observation 64d29288-d402-404d-ac17-e8ca288fd1d2 · outbound

This paper cites Behaviour4All: in-the-wild Facial Behaviour Analysis Toolkit.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Behaviour4All: in-the-wild Facial Behaviour Analysis Toolkit

Reference 34

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Observation abb7baf0-574d-4f61-8003-12ee12ec60e6 · outbound

This paper cites Advancements in affective and behavior analysis: The 8th abaw workshop and competi- tion,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition Advancements in affective and behavior analysis: The 8th abaw workshop and competi- tion,

Reference 35

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Observation 9dc5ead4-e678-4b75-a9eb-8329fa29f68d · outbound

This paper cites From emotions to violence: Multimodal fine-grained behavior analysis at the 9th abaw,.

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition From emotions to violence: Multimodal fine-grained behavior analysis at the 9th abaw,

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-02T07:10:38.234748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T07:10:38.234748Z digest=sha256:a56c3b6f3d9cd3d428a3e3c2e3cb82d0250c0a1ef20a84cf2d51b33607dddaa6

Pith citing papers

No inbound Pith citation observations are available.