Paper Citation Record · LEDGER

Efficient Transfer Learning for Video-language Foundation Models

As of 13 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2411.11223.

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

pith.paper-citation-record.v1
2411.11223 v4

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:51:32.331261Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

44 of 44 outbound references displayed

verified exact1
verified fuzzy29
unresolved14
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c05c3e24-0778-469d-a368-8a74ab018d5c · outbound

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

Efficient Transfer Learning for Video-language Foundation Models Quo vadis, action recognition? A new model and the kinetics dataset

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.941389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bc68abc1-ba72-4fbc-83c8-1793b0d665b7 · outbound

This paper cites A Short Note about Kinetics-600.

Efficient Transfer Learning for Video-language Foundation Models A Short Note about Kinetics-600

Reference 2

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Source-reported events for the cited work

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Observation 06def9af-1602-4a13-b661-b199d33f22f8 · outbound

This paper cites Conditional Prototype Rectification Prompt Learning.

Efficient Transfer Learning for Video-language Foundation Models Conditional Prototype Rectification Prompt Learning

Reference 3

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Observation 84871c5d-bd36-4ce6-9ab6-e5971deade99 · outbound

This paper cites Elaborative rehearsal for zero- shot action recognition.

Efficient Transfer Learning for Video-language Foundation Models Elaborative rehearsal for zero- shot action recognition

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.927182Z

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Observation 02df26ee-5fed-4ccd-af74-e1c2748f3e0c · outbound

This paper cites Adaptformer: Adapt- ing vision transformers for scalable visual recognition.

Efficient Transfer Learning for Video-language Foundation Models Adaptformer: Adapt- ing vision transformers for scalable visual recognition

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.914675Z

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Observation dd0a75b9-e3e4-428b-b984-d6f95203b989 · outbound

This paper cites OST: refining text knowledge with optimal spatio-temporal descriptor for general video recognition.

Efficient Transfer Learning for Video-language Foundation Models OST: refining text knowledge with optimal spatio-temporal descriptor for general video recognition

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.901484Z

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Observation 64169dcd-7543-40cd-b53a-7a7859339e53 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

Efficient Transfer Learning for Video-language Foundation Models DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 7

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Observation a73a580d-1cfc-47bd-8984-ce9645fcb818 · outbound

This paper cites BERT: pre-training of deep bidirectional trans- formers for language understanding.

Efficient Transfer Learning for Video-language Foundation Models BERT: pre-training of deep bidirectional trans- formers for language understanding

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.887646Z

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Observation 51e2781d-4dfb-4305-991d-d954ceaa4437 · outbound

This paper cites De- coupling zero-shot semantic segmentation.

Efficient Transfer Learning for Video-language Foundation Models De- coupling zero-shot semantic segmentation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.873866Z

Source-reported events for the cited work

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Observation d24d709d-cf16-48ae-8cd8-637ddf5e4aca · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Efficient Transfer Learning for Video-language Foundation Models An image is worth 16x16 words: Transformers for image recognition at scale

Reference 10

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Source-reported events for the cited work

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Observation c89b2d0f-cf04-4968-b43c-cda9938ac3f0 · outbound

This paper cites Zero-shot and few-shot video question answering with multi-modal prompts.

Efficient Transfer Learning for Video-language Foundation Models Zero-shot and few-shot video question answering with multi-modal prompts

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.851728Z

Source-reported events for the cited work

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Observation ef64be30-d0f7-4ecc-a849-f314d3d0eb7d · outbound

This paper cites Promptdet: Towards open-vocabulary detection using uncurated images.

Efficient Transfer Learning for Video-language Foundation Models Promptdet: Towards open-vocabulary detection using uncurated images

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.838213Z

Source-reported events for the cited work

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Observation 4f0f3511-9d45-4e68-9ea5-bb245398a014 · outbound

This paper cites The ”something something” video database for learning and evaluating visual common sense.

Efficient Transfer Learning for Video-language Foundation Models The ”something something” video database for learning and evaluating visual common sense

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.825448Z

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Observation c30ee68f-84f5-41f6-a264-a0002c0a3b52 · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level perfor- mance on imagenet classification.

Efficient Transfer Learning for Video-language Foundation Models Delving deep into rectifiers: Surpassing human-level perfor- mance on imagenet classification

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.811000Z

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Observation d44bca27-8f3d-493a-9aff-f5a3b43d41e0 · outbound

This paper cites Activitynet: A large-scale video bench- mark for human activity understanding.

Efficient Transfer Learning for Video-language Foundation Models Activitynet: A large-scale video bench- mark for human activity understanding

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.797187Z

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Observation a0b527de-e7ec-445c-aa64-96004d7203a7 · outbound

This paper cites Parameter-efficient transfer learning for NLP.

Efficient Transfer Learning for Video-language Foundation Models Parameter-efficient transfer learning for NLP

Reference 16

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Observation fb9340b1-89c0-49ca-8d43-cd58e4858111 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Efficient Transfer Learning for Video-language Foundation Models Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.768964Z

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Observation 0009498b-7b35-422f-88fa-d868da4253bd · outbound

This paper cites Prompting visual-language models for efficient video understanding.

Efficient Transfer Learning for Video-language Foundation Models Prompting visual-language models for efficient video understanding

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.756022Z

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Observation 2233691b-1772-495b-b8bc-66f9d17a9519 · outbound

This paper cites Khan, and Fahad Shahbaz Khan.

Efficient Transfer Learning for Video-language Foundation Models Khan, and Fahad Shahbaz Khan

Reference 19

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Observation 6fe6aa39-a558-40da-93cd-f0564bc07fdb · outbound

This paper cites Poggio, and Thomas Serre.

Efficient Transfer Learning for Video-language Foundation Models Poggio, and Thomas Serre

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.728632Z

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Observation 5f8e94e0-9fba-466a-a96c-785bfdd9c4c4 · outbound

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Efficient Transfer Learning for Video-language Foundation Models Unresolved cited work

Reference 21

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Observation b1f5c81a-c436-4ae8-8a69-dea6eea4028c · outbound

This paper cites Decoupled weight decay regularization.

Efficient Transfer Learning for Video-language Foundation Models Decoupled weight decay regularization

Reference 22

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Observation dcdf8144-d4b5-431f-8236-67c2c8e8532a · outbound

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Efficient Transfer Learning for Video-language Foundation Models Unresolved cited work

Reference 23

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Observation e7c95845-99dd-4121-a314-3af3bea6996b · outbound

This paper cites Expanding language-image pretrained models for general video recognition.

Efficient Transfer Learning for Video-language Foundation Models Expanding language-image pretrained models for general video recognition

Reference 24

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Observation f2ba8a1d-2690-4d1e-93e9-4de8e9658d3f · outbound

This paper cites St-adapter: Parameter-efficient image-to-video transfer learning.

Efficient Transfer Learning for Video-language Foundation Models St-adapter: Parameter-efficient image-to-video transfer learning

Reference 25

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Observation 2a9380f7-b780-4151-9c3f-689c1e994bc9 · outbound

This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

Efficient Transfer Learning for Video-language Foundation Models Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 26

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Observation 374f26f8-07b6-48d9-a5d2-1cd86c548d40 · outbound

This paper cites Haupt- mann.

Efficient Transfer Learning for Video-language Foundation Models Haupt- mann

Reference 27

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Source-reported events for the cited work

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Observation 0d756e45-12dc-4f09-a5e3-5c1ee58985c3 · outbound

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

Efficient Transfer Learning for Video-language Foundation Models Learning transferable visual models from natural language supervision

Reference 28

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Observation 8a18f7be-87a1-4fa1-90bf-1c4c2c66c01d · outbound

This paper cites Khan, and Fahad Shahbaz Khan.

Efficient Transfer Learning for Video-language Foundation Models Khan, and Fahad Shahbaz Khan

Reference 29

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Source-reported events for the cited work

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Observation cd0f600c-53c6-4a02-aefc-ffce390002b5 · outbound

This paper cites Consistency-guided prompt learning for vision-language models.

Efficient Transfer Learning for Video-language Foundation Models Consistency-guided prompt learning for vision-language models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.617576Z

Source-reported events for the cited work

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Observation a9605f1f-4c3d-4b1e-aad5-a329a9c4cddb · outbound

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

Efficient Transfer Learning for Video-language Foundation Models UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 31

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Observation f79f76ee-461f-4f68-9051-2391cd078b98 · outbound

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

Efficient Transfer Learning for Video-language Foundation Models Video- mae: Masked autoencoders are data-efficient learners for self-supervised video pre-training

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.604232Z

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Observation 51ae5c49-5551-4193-8894-c2e01e346428 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Efficient Transfer Learning for Video-language Foundation Models Representation Learning with Contrastive Predictive Coding

Reference 33

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Source-reported events for the cited work

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Observation f257c5ef-fb14-4fb8-b53a-c31a223251dc · outbound

This paper cites ActionCLIP: A New Paradigm for Video Action Recognition.

Efficient Transfer Learning for Video-language Foundation Models ActionCLIP: A New Paradigm for Video Action Recognition

Reference 34

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Source-reported events for the cited work

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Observation c447dbe6-346e-4474-ac13-16f21c6f1b55 · outbound

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

Efficient Transfer Learning for Video-language Foundation Models InternVideo: General Video Foundation Models via Generative and Discriminative Learning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T18:51:32.297314Z

Source-reported events for the cited work

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Observation 29ffe277-2538-41a7-b97b-982aa7d11776 · outbound

This paper cites Internvid: A large-scale video-text dataset for multimodal understanding and generation.

Efficient Transfer Learning for Video-language Foundation Models Internvid: A large-scale video-text dataset for multimodal understanding and generation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.590644Z

Source-reported events for the cited work

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Observation 2fac2da3-01b3-467d-99af-5091d5ddbd49 · outbound

This paper cites Khan, Fa- had Shahbaz Khan, and Mubarak Shah.

Efficient Transfer Learning for Video-language Foundation Models Khan, Fa- had Shahbaz Khan, and Mubarak Shah

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.576314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 17a54940-769a-48e2-9215-5c7565ea1cb1 · outbound

This paper cites Open-vclip: Transforming CLIP to an open-vocabulary video model via interpolated weight optimization.

Efficient Transfer Learning for Video-language Foundation Models Open-vclip: Transforming CLIP to an open-vocabulary video model via interpolated weight optimization

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.561506Z

Source-reported events for the cited work

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Observation 5a0174dd-4fa7-477b-a97e-061346b1add6 · outbound

This paper cites CORA: adapting CLIP for open-vocabulary detection with region prompting and anchor pre-matching.

Efficient Transfer Learning for Video-language Foundation Models CORA: adapting CLIP for open-vocabulary detection with region prompting and anchor pre-matching

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.548119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f6e9fd4c-d2e2-428e-b48b-7ef8972cf0ed · outbound

This paper cites MMA: multi-modal adapter for vision-language models.

Efficient Transfer Learning for Video-language Foundation Models MMA: multi-modal adapter for vision-language models

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.534607Z

Source-reported events for the cited work

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Observation 61b81311-cc84-437b-91f9-c8e6c963e082 · outbound

This paper cites AIM: adapting image models for efficient video action recognition.

Efficient Transfer Learning for Video-language Foundation Models AIM: adapting image models for efficient video action recognition

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.520390Z

Source-reported events for the cited work

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Observation 409cab93-66aa-40f5-8c71-e07c99cb1ee7 · outbound

This paper cites Florence: A New Foundation Model for Computer Vision.

Efficient Transfer Learning for Video-language Foundation Models Florence: A New Foundation Model for Computer Vision

Reference 42

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Observation 93e7e4cb-bf08-40b8-9098-95b03725c978 · outbound

This paper cites Tip- adapter: Training-free adaption of clip for few-shot classifica- tion.

Efficient Transfer Learning for Video-language Foundation Models Tip- adapter: Training-free adaption of clip for few-shot classifica- tion

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:51:32.506560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7844c60d-ab71-4bc1-a07b-e8d458cbb83e · outbound

This paper cites MoTE: Reconciling Generalization with Specialization for Visual-Language to Video Knowledge Transfer.

Efficient Transfer Learning for Video-language Foundation Models MoTE: Reconciling Generalization with Specialization for Visual-Language to Video Knowledge Transfer

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T18:51:32.331261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.