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Paper Citation Record · LEDGER

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection

As of 5 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2606.14096.

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

pith.paper-citation-record.v1
2606.14096 v2

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T05:16:56.297279Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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

48 of 48 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved44
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5898da60-a534-4e13-b5a2-cd07a9460885 · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 1

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Observation 4b93d302-857e-40d5-8566-6ebb75523525 · outbound

This paper cites Quo vadis, action recognition? a new model and the kinetics dataset,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Quo vadis, action recognition? a new model and the kinetics dataset,

Reference 2

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Observation c88b3a78-fdf3-4cb3-8796-1f10686f6262 · outbound

This paper cites The” something something.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection The” something something

Reference 3

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Observation e0acd069-00d3-4fc1-98ba-459580ba7e6a · outbound

This paper cites Slowfast networks for video recognition,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Slowfast networks for video recognition,

Reference 4

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Observation 7930c5f4-df87-4845-9b31-390e30260c29 · outbound

This paper cites Video swin transformer,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Video swin transformer,

Reference 5

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Observation 9fe270c6-78fe-4666-9e68-b87e46ad3998 · outbound

This paper cites Gpt4ego: unleashing the potential of pre-trained models for zero-shot egocentric action recognition,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Gpt4ego: unleashing the potential of pre-trained models for zero-shot egocentric action recognition,

Reference 6

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Observation 300f4fd6-6b2b-4b71-8885-9987505965bd · outbound

This paper cites Facial action units as a joint dataset training bridge for facial expression recognition,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Facial action units as a joint dataset training bridge for facial expression recognition,

Reference 7

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Observation 1a16d9bd-1f45-49ad-a20f-bb488f4c8744 · outbound

This paper cites Benchmarking micro-action recognition: Dataset, methods, and applications,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Benchmarking micro-action recognition: Dataset, methods, and applications,

Reference 8

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Observation 0cc23098-16b0-4dd6-9f90-ea9cdc1e5ae1 · outbound

This paper cites Mmad: Multi-label micro-action detection in videos,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Mmad: Multi-label micro-action detection in videos,

Reference 9

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Observation 07b32df5-aa3e-4ec0-9064-14446fc84a7f · outbound

This paper cites arXiv preprint arXiv:2603.26586 (2026).

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection arXiv preprint arXiv:2603.26586 (2026)

Reference 10

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Source-reported events for the cited work

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Observation 7238268a-fb85-454c-b754-0db341bb0db8 · outbound

This paper cites Motion matters: Motion-guided modulation network for skeleton-based micro- action recognition,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Motion matters: Motion-guided modulation network for skeleton-based micro- action recognition,

Reference 11

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Observation 5cba6665-22c0-4a8a-a08a-3ff874366835 · outbound

This paper cites Prototypical calibrating ambiguous samples for micro-action recogni- tion,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Prototypical calibrating ambiguous samples for micro-action recogni- tion,

Reference 12

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Observation 583d979b-5cae-4edf-860e-84fe75323085 · outbound

This paper cites imigue: An identity-free video dataset for micro-gesture understanding and emotion analysis,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection imigue: An identity-free video dataset for micro-gesture understanding and emotion analysis,

Reference 13

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Observation e2d64dde-bb40-4358-8fd1-9ac40e3daa99 · outbound

This paper cites Smg: A micro-gesture dataset towards spontaneous body gestures for emotional stress state analysis,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Smg: A micro-gesture dataset towards spontaneous body gestures for emotional stress state analysis,

Reference 14

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Observation d9175aec-b502-4621-a40e-00750e461721 · outbound

This paper cites Context-aware emotion recognition networks,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Context-aware emotion recognition networks,

Reference 15

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Observation 6d482143-f3ea-4328-9852-981083eab4e8 · outbound

This paper cites Samm: A spontaneous micro-facial movement dataset,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Samm: A spontaneous micro-facial movement dataset,

Reference 16

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Observation e61f3126-6280-45fd-b3e3-4999c86519b5 · outbound

This paper cites A spontaneous micro-expression database: Inducement, collection and baseline,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection A spontaneous micro-expression database: Inducement, collection and baseline,

Reference 17

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Observation 8bb6e78e-055a-476f-95d5-e4adc2099bf7 · outbound

This paper cites Casme database: A dataset of spontaneous micro-expressions collected from neutralized faces,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Casme database: A dataset of spontaneous micro-expressions collected from neutralized faces,

Reference 18

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Observation c6281a81-c367-4c74-a119-0622f6cd44c4 · outbound

This paper cites Cas (me) 2: a database for spontaneous macro-expression and micro-expression spotting and recognition,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Cas (me) 2: a database for spontaneous macro-expression and micro-expression spotting and recognition,

Reference 19

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Observation 91a632d8-ebb5-454a-8fd2-1a3be5a51ada · outbound

This paper cites Cas (me) 3: A third generation facial spontaneous micro- expression database with depth information and high ecological validity,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Cas (me) 3: A third generation facial spontaneous micro- expression database with depth information and high ecological validity,

Reference 20

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Observation 1974e0a6-5d91-4847-bf27-338e516be319 · outbound

This paper cites Ntu rgb+ d: A large scale dataset for 3d human activity analysis,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Ntu rgb+ d: A large scale dataset for 3d human activity analysis,

Reference 21

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Observation a24e7ec4-c366-4d34-b515-ab1cd739b597 · outbound

This paper cites Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding,

Reference 22

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Observation 9015ce8a-80e5-4f00-943b-77939c8b9c1f · outbound

This paper cites The epic-kitchens dataset: Collection, challenges and baselines,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection The epic-kitchens dataset: Collection, challenges and baselines,

Reference 23

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Observation 13282351-9020-4773-ba0c-24b5f2630445 · outbound

This paper cites Ego4d: Around the world in 3,000 hours of egocentric video,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Ego4d: Around the world in 3,000 hours of egocentric video,

Reference 24

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Observation 2a561a1f-7121-4c23-ae8f-ff086e3d59d3 · outbound

This paper cites To- wards student actions in classroom scenes: New dataset and baseline,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection To- wards student actions in classroom scenes: New dataset and baseline,

Reference 25

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Observation d3df70ac-702d-4fd8-af3b-34a60dacb7fd · outbound

This paper cites Casme ii: An improved spontaneous micro-expression database and the baseline evaluation,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Casme ii: An improved spontaneous micro-expression database and the baseline evaluation,

Reference 26

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Observation 3905d71f-2aa5-4110-a808-d3a2f0a509ed · outbound

This paper cites OpenDataLab: Empowering General Artificial Intelligence with Open Datasets.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection OpenDataLab: Empowering General Artificial Intelligence with Open Datasets

Reference 27

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Observation 26ecc31b-d409-483d-a53f-8eaeea6289c4 · outbound

This paper cites The epic- kitchens dataset: Collection, challenges and baselines,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection The epic- kitchens dataset: Collection, challenges and baselines,

Reference 28

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Observation c562234a-8d14-4f92-b919-8cea57eba38e · outbound

This paper cites Enhancing micro-video understanding by harnessing external sounds,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Enhancing micro-video understanding by harnessing external sounds,

Reference 29

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Observation 2e17c50d-0af7-409c-a42f-42d01fdfe485 · outbound

This paper cites Spatial temporal graph convolutional networks for skeleton-based action recognition,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Spatial temporal graph convolutional networks for skeleton-based action recognition,

Reference 30

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Observation 17e4cb3e-1c7e-4401-8f18-71578c7b0053 · outbound

This paper cites Revisiting skeleton- based action recognition,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Revisiting skeleton- based action recognition,

Reference 31

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Observation 651f6125-4692-4677-bff7-16a2211adf21 · outbound

This paper cites Pyskl: Towards good practices for skeleton action recognition,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Pyskl: Towards good practices for skeleton action recognition,

Reference 32

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Observation eb0d9dcf-b962-4a75-85ce-899adfe4355d · outbound

This paper cites Group contextualization for video recognition,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Group contextualization for video recognition,

Reference 33

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Observation e754e065-36c1-4a50-b6f8-2ec4da093851 · outbound

This paper cites Tsm: Temporal shift module for efficient video understanding,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Tsm: Temporal shift module for efficient video understanding,

Reference 34

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Observation ba2980e8-6bfc-4064-92d0-c6778c447ade · outbound

This paper cites Pointtad: Multi- label temporal action detection with learnable query points,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Pointtad: Multi- label temporal action detection with learnable query points,

Reference 35

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Observation ddb6d478-a6b0-4fa6-9523-01a9863f49e6 · outbound

This paper cites End-to-end temporal action detection with 1b parameters across 1000 frames,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection End-to-end temporal action detection with 1b parameters across 1000 frames,

Reference 36

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Observation 9bb0bd6e-80ea-4751-8a19-bf2e6b80addb · outbound

This paper cites Videomae: Masked autoen- coders are data-efficient learners for self-supervised video pre-training,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Videomae: Masked autoen- coders are data-efficient learners for self-supervised video pre-training,

Reference 37

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Observation 4e52180a-20a6-4ba8-aa0d-cf897a885ed0 · outbound

This paper cites The mastery of movement.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection The mastery of movement

Reference 38

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Observation 2e4a1dc3-fdb7-47bd-9cb6-6b67e57edf54 · outbound

This paper cites Emotion regulation through movement: unique sets of movement characteristics are associated with and enhance basic emotions,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Emotion regulation through movement: unique sets of movement characteristics are associated with and enhance basic emotions,

Reference 39

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Observation 6a520b4b-985d-4a91-9ce0-f9c6e92b7287 · outbound

This paper cites How do we recognize emotion from movement? specific motor components contribute to the recog- nition of each emotion,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection How do we recognize emotion from movement? specific motor components contribute to the recog- nition of each emotion,

Reference 40

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unresolved
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Observation 21a4b77f-54ed-47b1-bfe4-bc4aaf13a2cc · outbound

This paper cites Boosted lightface: A hybrid dnn and gbm model for boosted facial recognition,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Boosted lightface: A hybrid dnn and gbm model for boosted facial recognition,

Reference 41

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verified exact
arxiv_id, observed 2026-06-27T05:20:35.797600Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Observation 222a0b4f-25ec-49f0-bcb5-1ddbd9dc1c40 · outbound

This paper cites Qsgd: Communication-efficient sgd via gradient quantization and encoding,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Qsgd: Communication-efficient sgd via gradient quantization and encoding,

Reference 42

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Observation 2d761501-48de-4c88-9015-04426138b900 · outbound

This paper cites Actionformer: Localizing moments of actions with transformers,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Actionformer: Localizing moments of actions with transformers,

Reference 43

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no resolver link, observed 2026-06-27T05:16:56.297279Z

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Unavailable: canonical work link unavailable.

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Observation 9146f921-8801-4dfd-8e93-ce08a0e1122b · outbound

This paper cites Diagnosing error in temporal action detectors,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Diagnosing error in temporal action detectors,

Reference 44

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d5966904-bd25-4f69-ba79-ac3303d0e974 · outbound

This paper cites An information-theoretic perspective of tf–idf measures,.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection An information-theoretic perspective of tf–idf measures,

Reference 45

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unresolved
no resolver link, observed 2026-06-27T05:16:56.297279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T05:16:56.297279Z digest=sha256:1ae1634a553f651b4db2bd47d118ce5a62bbacea9bb8909459533067bab06d47

Observation 5bdedc21-a9d9-4c65-8a31-84dfa7e3cf8e · outbound

This paper cites The baseline achieves a low FN in most dimensions.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection The baseline achieves a low FN in most dimensions

Reference 46

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T05:16:56.297279Z digest=sha256:37545d0e302c0c98b44dc53bb87e1f3af84c42c2c4a60c462842b2178f787a38

Observation 2d438a3d-4097-42ae-a26a-3bbf924ea136 · outbound

This paper cites Confusion Error.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Confusion Error

Reference 47

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T05:16:56.297279Z digest=sha256:0a77bac49ef2b724c29a291f2aff02bc6362076e64fbdfaaf3bcc5fbdaf82205

Observation cf6b36de-29b7-4c35-87d2-26e06bf7caf6 · outbound

This paper cites Retracting and stretching arms.

A New Multi-Domain Benchmark for Micro-Action Recognition and Detection Retracting and stretching arms

Reference 48

Resolution
unresolved
no resolver link, observed 2026-06-27T05:16:56.297279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.