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Paper Citation Record · LEDGER

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition

As of 15 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 1 inbound Pith citation observation for arXiv:2411.19041.

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

pith.paper-citation-record.v1
2411.19041 v2

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:41:52.389174Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-17T22:31:13.391859Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T22:32:10.995864Z

Reference resolution

64 of 64 outbound references displayed

  • verified exact1
  • verified fuzzy54
  • unresolved8
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d03c3966-b7b4-498b-b70a-5e7327f072dd · outbound

This paper cites StyleDomain: Efficient and lightweight parameteriza- tions of StyleGAN for one-shot and few-shot domain adap- tation.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition StyleDomain: Efficient and lightweight parameteriza- tions of StyleGAN for one-shot and few-shot domain adap- tation

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c81721e7-2b96-452d-9ed6-4d1500a50fc1 · outbound

This paper cites ViViT: A video vision transformer.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition ViViT: A video vision transformer

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation befc249e-a94a-4c71-8033-36467cb715a5 · outbound

This paper cites TARN: Temporal attentive relation network for few-shot and zero-shot action recognition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition TARN: Temporal attentive relation network for few-shot and zero-shot action recognition

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 03ca64df-42e1-4e30-afb1-78486075ad90 · outbound

This paper cites Pattern recognition and machine learning.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Pattern recognition and machine learning

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation f6f61c86-6b50-43dc-8c28-b22491a549e8 · outbound

This paper cites Few-shot action recognition with implicit temporal alignment and pair similarity optimization.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Few-shot action recognition with implicit temporal alignment and pair similarity optimization

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e6c58cc5-d1e8-4af8-b71c-a24fb42e78b4 · outbound

This paper cites Few-shot video classification via tempo- ral alignment.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Few-shot video classification via tempo- ral alignment

Reference 6

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e79aafc2-6021-4ff2-95b0-bfe2baf1302a · outbound

This paper cites Quo vadis, Action Recognition? A new model and the kinetics dataset.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Quo vadis, Action Recognition? A new model and the kinetics dataset

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 70a11b78-8b49-47f1-9e59-7d90be106f87 · outbound

This paper cites Tem- adapter: Adapting image-text pretraining for video question answer.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Tem- adapter: Adapting image-text pretraining for video question answer

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7fc877b9-d9d3-4244-8945-5283d1b277a8 · outbound

This paper cites Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 01c2cc31-a00a-4e9b-8b73-a6fdb56df9d4 · outbound

This paper cites ImageNet: A large-scale hierarchical image database.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition ImageNet: A large-scale hierarchical image database

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation bb064e9d-9461-47cb-a4e8-b5b2f7e7157f · outbound

This paper cites Tuning pre-trained model via moment probing.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Tuning pre-trained model via moment probing

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ac781967-87e1-49eb-986c-8f817598dcca · outbound

This paper cites Exploring the cross-domain action recognition prob- lem by deep feature learning and cross-domain learning.IEEE Access, 6:68989–69008, 2018.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Exploring the cross-domain action recognition prob- lem by deep feature learning and cross-domain learning.IEEE Access, 6:68989–69008, 2018

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 2609d7b5-2ff4-450e-87f6-98982c482249 · outbound

This paper cites A pairwise attentive adversarial spatiotemporal network for cross-domain few-shot action recognition-R2.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition A pairwise attentive adversarial spatiotemporal network for cross-domain few-shot action recognition-R2

Reference 13

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b1838c3f-a8ac-42cd-8917-4aa437bc4636 · outbound

This paper cites A novel multiple-view adversarial learning network for unsupervised domain adaptation action recog- nition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition A novel multiple-view adversarial learning network for unsupervised domain adaptation action recog- nition

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 1001e78a-1b72-484e-bfe7-d76a8f2fc17b · outbound

This paper cites Towards better robustness against common corruptions for unsupervised domain adaptation.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Towards better robustness against common corruptions for unsupervised domain adaptation

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 38597f82-6e06-47a8-aedf-4c6d7da93d1c · outbound

This paper cites Something Something.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Something Something

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 1979dec1-0e7a-471c-b47c-2550150c0b88 · outbound

This paper cites Con- sistency prototype module and motion compensation for few- shot action recognition (CLIP-CPM 2C).

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Con- sistency prototype module and motion compensation for few- shot action recognition (CLIP-CPM 2C)

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 06893d35-5738-4d3f-8e1e-68216b12c6ed · outbound

This paper cites DMSD-CDFSAR: Distillation from mixed-source domain for cross-domain few-shot action recognition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition DMSD-CDFSAR: Distillation from mixed-source domain for cross-domain few-shot action recognition

Reference 18

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raw_fallback, observed 2026-08-12T10:41:52.961445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 0ee90e67-b708-427c-86d3-817741ed1297 · outbound

This paper cites Codella, Leonid Karlinsky, James V.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Codella, Leonid Karlinsky, James V

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 45d6a638-a362-4cb3-92cf-9d0415151dca · outbound

This paper cites Masked autoencoders are scalable vision learners.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Masked autoencoders are scalable vision learners

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 3640f397-9e85-463a-960e-53aea34f1051 · outbound

This paper cites Parameter-efficient transfer learning for NLP.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Parameter-efficient transfer learning for NLP

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 738c7053-c68b-4627-bfea-c736e742c42f · outbound

This paper cites Dy- namic distillation network for cross-domain few-shot recog- nition with unlabeled data.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Dy- namic distillation network for cross-domain few-shot recog- nition with unlabeled data

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.230362Z digest=sha256:dc0db48438e98ccbfa3a21f1e1aba8b497571370a3f25204cef02860df71e5f5

Observation c6e42d69-0fe8-4903-8935-fe23cae2091c · outbound

This paper cites Kuehne, H.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Kuehne, H

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation cb5005d1-a31f-4ed7-b908-3d9030c622e8 · outbound

This paper cites UniFormerV2: Unlocking the 9 potential of image vits for video understanding.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition UniFormerV2: Unlocking the 9 potential of image vits for video understanding

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.896672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.237595Z digest=sha256:57fe367aeff7e9a909a226c101ce63708ad162893f6a7586d5f49a4c6c4d353e

Observation ed8ce010-5ef5-49b6-8576-49b1407b9b32 · outbound

This paper cites RESOUND: To- wards action recognition without representation bias.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition RESOUND: To- wards action recognition without representation bias

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.886041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.241195Z digest=sha256:d0aa209180febe5fa2fc2bac71f4fd0b079a44a108b22426e84d5f2fe56970eb

Observation 8d77ec7a-d311-4af2-a727-c89f88dc797a · outbound

This paper cites Scaling & shifting your features: A new baseline for efficient model tuning.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Scaling & shifting your features: A new baseline for efficient model tuning

Reference 26

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.244716Z digest=sha256:21c024466d35c3dbd1527c833f29cbc89c50f507504aa40b6e735827e5fd55d9

Observation 7e99c0be-09af-4fed-a89d-121e1cd530f4 · outbound

This paper cites Deep quality assessment of com- pressed videos: A subjective and objective study.IEEE Trans- actions on Circuits and Systems for Video Technology, 33(6): 2616–2626, 2023.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Deep quality assessment of com- pressed videos: A subjective and objective study.IEEE Trans- actions on Circuits and Systems for Video Technology, 33(6): 2616–2626, 2023

Reference 27

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raw_fallback, observed 2026-08-12T10:41:52.864227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.248329Z digest=sha256:9fa7f88ba2405c8afdbc20193bc76feb555968cfbbe3649921de1297383d4c2e

Observation 390d0bb9-281a-48c0-ab53-5761d35fac7c · outbound

This paper cites MASTAF: A model-agnostic spatio-temporal attention fusion network for few-shot video classification.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition MASTAF: A model-agnostic spatio-temporal attention fusion network for few-shot video classification

Reference 28

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raw_fallback, observed 2026-08-12T10:41:52.851770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.252061Z digest=sha256:75b2381df2510b5fddd3f9e509a0bb923d3a4eb4742a0f7d65a73d813853ea06

Observation c061ede7-aee9-4395-940f-21af19ce1375 · outbound

This paper cites TAM: Temporal adaptive module for video recognition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition TAM: Temporal adaptive module for video recognition

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.840819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.256137Z digest=sha256:d924b45493a7288d86cf5534ec76f1dab8804c7541dee43885b2770c9259c756

Observation 5991fad7-99e4-40f9-a0dd-90337a5ad880 · outbound

This paper cites Fine-grained unsupervised do- main adaptation for gait recognition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Fine-grained unsupervised do- main adaptation for gait recognition

Reference 30

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raw_fallback, observed 2026-08-12T10:41:52.828973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.259617Z digest=sha256:3a4899dab720bee6006e49c96dc92227abedbbbbd0987c2846137b9b0c2430d4

Observation ca28380d-225e-4dbf-b815-f7cbd5da102d · outbound

This paper cites RareAct: A video dataset of unusual interactions.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition RareAct: A video dataset of unusual interactions

Reference 31

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unresolved
no resolver link, observed 2026-08-12T10:41:52.263073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a21be97b-0fe7-4504-8eb7-afd0812a1e94 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition DINOv2: Learning Robust Visual Features without Supervision

Reference 32

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unresolved
no resolver link, observed 2026-08-12T10:41:52.266932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ce45bf6e-ba3a-4199-9f3f-39841d9e8a22 · outbound

This paper cites ST-Adapter: Parameter-efficient image-to-video transfer learning.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition ST-Adapter: Parameter-efficient image-to-video transfer learning

Reference 33

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raw_fallback, observed 2026-08-12T10:41:52.816342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.270972Z digest=sha256:db6d25605fcb28ab6817b58f911e02d6373baf9e4a75d77ed4b2ba6ae054e244

Observation 865703a7-d1e1-40e8-b691-fe7869309afa · outbound

This paper cites Temporal-relational cross Transformers for few-shot action recognition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Temporal-relational cross Transformers for few-shot action recognition

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.804839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.275791Z digest=sha256:d271e9bf55d73a91120ff4c295681f9d1fa8f6a0373a4f1bfbc25994068de089

Observation 4a540729-a7ae-4a17-a85f-b20c5f04f8e3 · outbound

This paper cites Self-training for few-shot transfer across extreme task differences.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Self-training for few-shot transfer across extreme task differences

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.793459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.280195Z digest=sha256:8a930baa5058b931560415adb58f04a71711e34540286b46f878742487a890a5

Observation fb95b448-324a-4593-b961-8c9e050e9c1a · outbound

This paper cites an unresolved cited work.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:41:52.782423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.284157Z digest=sha256:b9dbf60fd9f79f6a8c23d93a05fe50ac8c994e4b713f117076e973b03a9bb7df

Observation 9ab54372-b61f-4330-a98e-e3e90476c576 · outbound

This paper cites Contrast with reconstruct: Contrastive 3D representation learning guided by generative pretraining.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Contrast with reconstruct: Contrastive 3D representation learning guided by generative pretraining

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.770529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.287776Z digest=sha256:410ddf8c83124a9bb5bae588ecffd5a5289fec02487241802e512cdfaf24b187

Observation 22d3173b-d3b5-4cfa-b6f3-cac719cd8083 · outbound

This paper cites Learning transferable visual models from natural language supervision.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Learning transferable visual models from natural language supervision

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.759686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.291612Z digest=sha256:c1ee82f55708e113a24c796b3e77fbe9073eeaf1c1faf15666c530ac77a13948

Observation 9b3fefd7-7ead-4bda-b3af-93387193cda5 · outbound

This paper cites CDFSL-V: Cross-domain few-shot learning for videos.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition CDFSL-V: Cross-domain few-shot learning for videos

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.746975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.295494Z digest=sha256:30b8cf435ba405b2efa96de4344408543f658e295399757de15dc05e35eed117

Observation 10f37aa2-774b-42d4-9282-604fe3ada1f3 · outbound

This paper cites Com- monsense knowledge prompting for few-shot action recogni- tion in videos.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Com- monsense knowledge prompting for few-shot action recogni- tion in videos

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.735091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.299117Z digest=sha256:928fa87a478a9616b7e5cc93e5771c6ee54b3f3fd32d56ae4ce6fb1f13f603b2

Observation 59ef85c7-0b57-493e-bf58-85677469c35b · outbound

This paper cites Prototypical networks for few-shot learning.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Prototypical networks for few-shot learning

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.723643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.302685Z digest=sha256:c5b4a2d7df511cd508ffb61c65f2812f474f569c8270b884e61ef9a7c9a7fc7a

Observation 1ec7d5d1-c1f5-423a-8b8c-22bc0add1bdc · outbound

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

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-12T10:41:52.306070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:52.306070Z digest=sha256:f17016ecf677146d93df492ce23445eb378383bce2699f54404759e3b206f3e9

Observation 40e86561-981c-49c7-a427-f1d2c2bfc743 · outbound

This paper cites Spatio-temporal relation modeling for few-shot action recognition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Spatio-temporal relation modeling for few-shot action recognition

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.713218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.309975Z digest=sha256:64bc7fc51153aa5dbf0ceb41d8099057f2422492d27a7f61380858929ea4f757

Observation 6c2248df-2e0a-4a5e-95b1-99a5e3593dd9 · outbound

This paper cites Video- MAE: Masked autoencoders are data-efficient learners for self-supervised video pre-training.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Video- MAE: Masked autoencoders are data-efficient learners for self-supervised video pre-training

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.703059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.313536Z digest=sha256:aae965a58b279aa459bb73b32a829d7f0086364e95f8cc4d20cbdb80ec1295a9

Observation 908ce6f9-9e8a-4cfd-8528-ba76ca15a342 · outbound

This paper cites VideoMAE V2: Scaling video masked autoencoders with dual masking.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition VideoMAE V2: Scaling video masked autoencoders with dual masking

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.693321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.317129Z digest=sha256:a14e2eeac52950263b66049878a692917103beebad17184bce5f08d06b05d605

Observation 7b9ed767-b234-4117-bb3b-a2e01ebac9b9 · outbound

This paper cites Hybrid relation guided set matching for few-shot action recog- nition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Hybrid relation guided set matching for few-shot action recog- nition

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.681635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.320837Z digest=sha256:bb585f761efab8f407860c20b7935c69e087dae1ea22572eca79c41ee8594567

Observation bd44164b-bdf5-49e6-8748-15ced870c131 · outbound

This paper cites Few-shot learning meets transformer: Unified query-support transform- ers for few-shot classification.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Few-shot learning meets transformer: Unified query-support transform- ers for few-shot classification

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.670312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.325131Z digest=sha256:54f7a5018602848dc2c73f704c2b1a6a7043f9e677635fa03442c13bc5cb15f2

Observation 0465652b-dbb1-435e-a39e-2e85575855ba · outbound

This paper cites Task- aware dual-representation network for few-shot action recog- 10 nition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Task- aware dual-representation network for few-shot action recog- 10 nition

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.658182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.329634Z digest=sha256:ca208c3802e8198f75809d3d0c1fcbd40a1068ba587abb96e750f80110ec8c9b

Observation f79071a4-47e0-4529-86c2-65c54117eaa6 · outbound

This paper cites MoLo: Motion- augmented long-short contrastive learning for few-shot action recognition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition MoLo: Motion- augmented long-short contrastive learning for few-shot action recognition

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.646218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.333073Z digest=sha256:c651bf5dcda880115fc85acf92ec0e9c3f2f555a63b6f28026709dffd82ea6d9

Observation 0be148b3-5373-45e6-af72-6443dc9f0cad · outbound

This paper cites Cross-domain few-shot ac- tion recognition with unlabeled videos.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Cross-domain few-shot ac- tion recognition with unlabeled videos

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.635494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.336466Z digest=sha256:d592636c72f398ab31dd1d1bdc4a7d5afdb0b13aa89a2c5716f18ae8444fae25

Observation b688cc8b-db2e-44e1-bd87-887df2dce224 · outbound

This paper cites Few-shot Action Recognition with Captioning Foundation Models.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Few-shot Action Recognition with Captioning Foundation Models

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T10:41:52.340037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:52.340037Z digest=sha256:76c18ce92bdd27eaa313e891c24e50f73a81a3017904567a2a4de98695061f61

Observation 6ebbef3a-9ca9-4090-a545-3d4c6f672aa4 · outbound

This paper cites Few-shot action recognition via multi-view represen- tation learning.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Few-shot action recognition via multi-view represen- tation learning

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.624897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.344131Z digest=sha256:82a5a9475ba49243cccc3fa99a1abf773a54e8621116ba46078ce9aad60f05a9

Observation a918c23d-77a4-46eb-94ab-dcdf821fd69d · outbound

This paper cites CLIP-guided prototype modulating for few-shot action recognition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition CLIP-guided prototype modulating for few-shot action recognition

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.613809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.348334Z digest=sha256:402f2bed8fba64329e264b7dbabee49e931c2b1da60e328a4afcd36490ea8398

Observation cab6c30c-7327-4ee4-8dce-62aa30aa84cc · outbound

This paper cites InternVideo: General Video Foundation Models via Generative and Discriminative Learning.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition InternVideo: General Video Foundation Models via Generative and Discriminative Learning

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-12T10:41:52.352174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:41:52.352174Z digest=sha256:2384c30b3df3e211275d4d9e399bf3411787df6632ac4c45802a0c1c00865a8b

Observation 39578c4f-fd3a-4487-a8d9-9e133d7f4de2 · outbound

This paper cites Active exploration of multimodal complemen- tarity for few-shot action recognition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Active exploration of multimodal complemen- tarity for few-shot action recognition

Reference 55

Resolution
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raw_fallback, observed 2026-08-12T10:41:52.603400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.356195Z digest=sha256:8978a0c4d0e6ec291122f039c570b6ed7d95bfd4ac391de875745869c408902f

Observation c894b60d-2e03-4e10-b39f-da371ada7f74 · outbound

This paper cites Boosting few-shot action recognition with graph- guided hybrid matching.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Boosting few-shot action recognition with graph- guided hybrid matching

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.592275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.359653Z digest=sha256:91540d7ecfdeb3d13fd9bbd759fb238f084e10d8fdc82c0653f51b30d3bad89f

Observation 7e6834b3-316a-4290-8d37-1e4d87debc7d · outbound

This paper cites Multiview Trans- formers for video recognition.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Multiview Trans- formers for video recognition

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.581567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.363821Z digest=sha256:b84b615e40c4e512d6375976128a8850b2a2dd015d2b308706ef9db209b1029b

Observation b889b480-70d6-40b7-9c10-b04671ba000d · outbound

This paper cites Learning implicit temporal alignment for few-shot video classification.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Learning implicit temporal alignment for few-shot video classification

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.569961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.367225Z digest=sha256:be432fc86e0e29cc7a153846d4b04d9e6600ddf6c3a98e9cec9a7ef6ed9b8fdd

Observation 59395302-5f91-4b02-8161-1e4d9600c342 · outbound

This paper cites Image BERT pre-training with online tokenizer.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Image BERT pre-training with online tokenizer

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.557327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.371140Z digest=sha256:c392edf18777dfb2d338297896b97ece24cd9e02bdc0f6c6962b66c32d81f069

Observation 73a6b65a-7348-441c-a13c-20194bd9e17b · outbound

This paper cites Compound memory networks for few-shot video classification.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Compound memory networks for few-shot video classification

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.545396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.374871Z digest=sha256:3121ef02fd2a6aa9f096c2a6e45d3806218f3b153405c82952dbf05c7e2b9c79

Observation 949880d9-3a01-472b-8d48-aeeaf5cb44f0 · outbound

This paper cites an unresolved cited work.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Unresolved cited work

Reference 62

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:41:52.523391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.381838Z digest=sha256:db615fa6298f23b48ee1021f7305a31ce1216fa1253e2c2686584e86470dd1ab

Observation add09149-12fa-4f1b-895b-24d0e2100efb · outbound

This paper cites Playing cards.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Playing cards

Reference 63

Resolution
malformed identifier
raw_fallback, observed 2026-08-12T10:41:52.511518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.385364Z digest=sha256:64160a4ab08c86d50c442cae345d1a5bcd185aa3f00dba0d8febc620f9e0857e

Observation b9e195e2-27a5-4b5b-9d0e-d30491f66f94 · outbound

This paper cites Hammer phone.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Hammer phone

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:41:52.499412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.389174Z digest=sha256:cb4304507afa06de375933b7a23eff8a90a6bc59a2d9ea8555efa366aba699bc

Observation 462c50b1-9f60-4431-9c27-40e87be39ad9 · outbound

This paper cites an unresolved cited work.

TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition Unresolved cited work

Reference 2018

Resolution
unresolved
raw_fallback, observed 2026-08-12T10:41:52.534588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T10:41:52.378555Z digest=sha256:18acfbf9241ff0a13821edb0f5bd53e921fd6174e1fcfbe1848269e932c84fe7

Pith citing papers

Observation 9c3c84c2-cb27-4f7a-b8b3-86a739b22ded · inbound

Uni-Hand: Universal Hand Motion Forecasting in Egocentric Views cites this paper.

Uni-Hand: Universal Hand Motion Forecasting in Egocentric Views TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:32:10.999064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-17T22:31:13.391859Z digest=sha256:d5306a31c6cdbd0ffa9de00c64fd83870e9920d96c0b2d7ed9ba20c349951ac1