ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos | Paper Citation Record

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This paper cites GPT-4 Technical Report.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos GPT-4 Technical Report

Reference 1

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This paper cites Ht-step: Aligning instructional articles with how-to videos.Advances in Neural Information Processing Systems, 36, 2024.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Ht-step: Aligning instructional articles with how-to videos.Advances in Neural Information Processing Systems, 36, 2024

Reference 2

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This paper cites Exploring synonyms as context in zero-shot action recognition.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Exploring synonyms as context in zero-shot action recognition

Reference 3

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This paper cites Hiervl: Learning hierarchical video- language embeddings.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Hiervl: Learning hierarchical video- language embeddings

Reference 4

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This paper cites The ikea asm dataset: Understanding people assem- bling furniture through actions, objects and pose.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos The ikea asm dataset: Understanding people assem- bling furniture through actions, objects and pose

Reference 5

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This paper cites Is space-time attention all you need for video understanding? In ICML, volume 2, page 4, 2021.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Is space-time attention all you need for video understanding? In ICML, volume 2, page 4, 2021

Reference 6

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This paper cites Rethinking zero-shot video classification: End-to-end training for realistic applications.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Rethinking zero-shot video classification: End-to-end training for realistic applications

Reference 7

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Observation ff4d3c15-0b5a-44a9-8445-fed95ac1fa51 · outbound

This paper cites Regen: A good generative zero-shot video classifier should be rewarded.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Regen: A good generative zero-shot video classifier should be rewarded

Reference 8

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

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Quo vadis, action recognition? a new model and the kinetics dataset

Reference 9

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

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Elaborative rehearsal for zero-shot action recognition

Reference 10

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This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 11

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This paper cites Teaching structured vision & language concepts to vision & language models.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Teaching structured vision & language concepts to vision & language models

Reference 12

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This paper cites Step- former: Self-supervised step discovery and localization in instructional videos.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Step- former: Self-supervised step discovery and localization in instructional videos

Reference 13

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Observation 2fec3f59-f902-4123-84b1-945a3c7abf3e · outbound

This paper cites Zero-shot action recognition in videos: A survey.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Zero-shot action recognition in videos: A survey

Reference 14

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This paper cites Ms-tcn: Multi-stage tem- poral convolutional network for action segmentation.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Ms-tcn: Multi-stage tem- poral convolutional network for action segmentation

Reference 15

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Observation bea9a6b6-a870-40a8-bd16-a779afd8df73 · outbound

This paper cites Learning to recognize objects in egocentric activities.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Learning to recognize objects in egocentric activities

Reference 16

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Observation d9e4b6be-e75c-4f34-9bd5-bfb91ebfc51d · outbound

This paper cites Slowfast networks for video recognition.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Slowfast networks for video recognition

Reference 17

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Observation 9e8b1f8f-6ab6-4707-8485-c0dbb80803cd · outbound

This paper cites Prego: online mistake detection in procedural ego- centric videos.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Prego: online mistake detection in procedural ego- centric videos

Reference 18

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Observation 1d271bf2-ada1-4cb9-81a9-db6c660651a9 · outbound

This paper cites Improving zero-shot gen- eralization and robustness of multi-modal models.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Improving zero-shot gen- eralization and robustness of multi-modal models

Reference 19

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This paper cites Weakly-supervised action segmentation and unseen error detection in anomalous instructional videos.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Weakly-supervised action segmentation and unseen error detection in anomalous instructional videos

Reference 20

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

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Ego4d: Around the world in 3,000 hours of egocentric video

Reference 21

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Observation 90c21025-a295-4590-91b0-ee49897d6703 · outbound

This paper cites Temporal alignment networks for long-term video.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Temporal alignment networks for long-term video

Reference 22

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This paper cites Probing Image-Language Transformers for Verb Understanding.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Probing Image-Language Transformers for Verb Understanding

Reference 23

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Observation ac89540c-787a-4938-a1f6-9275e2aa9601 · outbound

This paper cites Clover: Towards a unified video-language alignment and fusion model.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Clover: Towards a unified video-language alignment and fusion model

Reference 24

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Observation be5709eb-168f-4b2c-940d-cbf8a686689b · outbound

This paper cites Fine-grained generalized zero-shot learning via dense attribute-based attention.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Fine-grained generalized zero-shot learning via dense attribute-based attention

Reference 25

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Observation 74b88be9-9871-4bae-b5b4-d24e6670ea2b · outbound

This paper cites Objects2action: Classifying and localiz- ing actions without any video example.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Objects2action: Classifying and localiz- ing actions without any video example

Reference 26

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Observation e9921a13-86a5-40c0-af2e-6a837086a824 · outbound

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

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Prompting visual-language models for efficient video understanding

Reference 27

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This paper cites Error detection in egocentric procedural task videos.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Error detection in egocentric procedural task videos

Reference 28

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This paper cites Align and prompt: Video-and-language pre-training with entity prompts.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Align and prompt: Video-and-language pre-training with entity prompts

Reference 29

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This paper cites Cross-modal representation learning for zero- shot action recognition.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Cross-modal representation learning for zero- shot action recognition

Reference 30

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This paper cites Match, expand and im- prove: Unsupervised finetuning for zero-shot action recog- nition with language knowledge.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Match, expand and im- prove: Unsupervised finetuning for zero-shot action recog- nition with language knowledge

Reference 31

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Observation bb8f3bb8-0369-4a79-ba98-800b5391f2a3 · outbound

This paper cites Learning to recognize procedural activities with distant supervision.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Learning to recognize procedural activities with distant supervision

Reference 32

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This paper cites Out-of-distribution detection for gener- alized zero-shot action recognition.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Out-of-distribution detection for gener- alized zero-shot action recognition

Reference 33

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Observation f768d3f8-f83e-4dc0-8c91-00a35ec1b7e3 · outbound

This paper cites Learning to ground instructional articles in videos through narrations.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Learning to ground instructional articles in videos through narrations

Reference 34

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This paper cites Object priors for classifying and localizing unseen actions.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Object priors for classifying and localizing unseen actions

Reference 35

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This paper cites End-to-end learning of visual representations from uncurated instruc- tional videos.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos End-to-end learning of visual representations from uncurated instruc- tional videos

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This paper cites Howto100m: Learning a text-video embedding by watching hundred million narrated video clips, 2019.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Howto100m: Learning a text-video embedding by watching hundred million narrated video clips, 2019

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This paper cites Efficient Estimation of Word Representations in Vector Space.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Efficient Estimation of Word Representations in Vector Space

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This paper cites Verbs in action: Improving verb understanding in video-language models.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Verbs in action: Improving verb understanding in video-language models

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This paper cites Spoken moments: Learning joint audio-visual representations from video descriptions.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Spoken moments: Learning joint audio-visual representations from video descriptions

Reference 40

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This paper cites Zero-shot temporal action detection via vision-language prompting.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Zero-shot temporal action detection via vision-language prompting

Reference 41

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

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Expanding language-image pretrained models for gen- eral video recognition

Reference 42

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This paper cites Learning multimodal representations for unseen activities.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Learning multimodal representations for unseen activities

Reference 43

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This paper cites Egovlpv2: Egocentric video-language pre-training with fusion in the backbone.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Egovlpv2: Egocentric video-language pre-training with fusion in the backbone

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Observation 5efc7eac-01e5-4a80-a6f9-02e7aae9ae5e · outbound

This paper cites What does a platypus look like? generating customized prompts for zero-shot image classification.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos What does a platypus look like? generating customized prompts for zero-shot image classification

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This paper cites Alignment-uniformity aware representation learning for zero-shot video classifica- tion.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Alignment-uniformity aware representation learning for zero-shot video classifica- tion

Reference 46

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Observation 08ddf227-795d-407f-a990-67c7f1f1ef5e · outbound

This paper cites Rethinking zero-shot action recognition: Learning from latent atomic actions.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Rethinking zero-shot action recognition: Learning from latent atomic actions

Reference 47

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Observation 28f404fb-d0db-4909-bc7a-7117967cc0c3 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Learning transferable visual models from natural language supervi- sion

Reference 48

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This paper cites Language-based action concept spaces improve video self-supervised learn- ing.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Language-based action concept spaces improve video self-supervised learn- ing

Reference 49

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Observation 60c15b2d-c2ce-4b4c-abcd-b2b204a7c148 · outbound

This paper cites Fine-tuned clip models are efficient video learners.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Fine-tuned clip models are efficient video learners

Reference 50

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This paper cites Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning

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Observation 2aaf919a-3816-4afe-bbb6-cd3f35a5bd35 · outbound

This paper cites As- sembly101: A large-scale multi-view video dataset for un- derstanding procedural activities.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos As- sembly101: A large-scale multi-view video dataset for un- derstanding procedural activities

Reference 52

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This paper cites Mpnet: Masked and permuted pre-training for language understanding.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Mpnet: Masked and permuted pre-training for language understanding

Reference 53

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Observation 43391558-a256-44fc-9939-dd713ce37841 · outbound

This paper cites Coin: A large-scale dataset for comprehensive instructional video analysis.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Coin: A large-scale dataset for comprehensive instructional video analysis

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:08:43.295076Z

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

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos ActionCLIP: A New Paradigm for Video Action Recognition

Reference 55

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ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Vilta: Enhancing vision-language pre-training through textual augmentation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:08:43.235796Z

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This paper cites Pax- ion: Patching action knowledge in video-language founda- tion models.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Pax- ion: Patching action knowledge in video-language founda- tion models

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:08:43.152810Z

Source-reported events for the cited work

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Observation 002a0166-01aa-4425-8f9b-4ebf5272c2d3 · outbound

This paper cites Zero-shot event detection using multi-modal fusion of weakly supervised concepts.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Zero-shot event detection using multi-modal fusion of weakly supervised concepts

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:08:43.059961Z

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Observation fa7edda3-578f-463d-942c-58c3ed6cb094 · outbound

This paper cites Cap4video: What can auxiliary captions do for text-video retrieval? In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages 10704–10713, 2023.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Cap4video: What can auxiliary captions do for text-video retrieval? In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages 10704–10713, 2023

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:08:42.945797Z

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Observation d8a3b65a-cb63-4822-9401-d98af018659b · outbound

This paper cites Revisiting clas- sifier: Transferring vision-language models for video recog- nition.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Revisiting clas- sifier: Transferring vision-language models for video recog- nition

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:08:42.879421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d61984bc-1b77-4ae9-894d-e0c97895b061 · outbound

This paper cites Bidirectional cross- modal knowledge exploration for video recognition with pre-trained vision-language models.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Bidirectional cross- modal knowledge exploration for video recognition with pre-trained vision-language models

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:08:42.835387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cb7ad621-edbc-4d41-8701-0aad67f7b9c2 · outbound

This paper cites Generative action description prompts for skeleton-based action recognition.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Generative action description prompts for skeleton-based action recognition

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:08:42.651926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 31beffb7-5a7b-4c4d-b56c-48ca0150bb0e · outbound

This paper cites VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-12T14:08:42.293896Z

Source-reported events for the cited work

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Observation cb277bc7-0b42-4946-9107-b6beed78ed43 · outbound

This paper cites Movie genre classification by language augmentation and shot sampling.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Movie genre classification by language augmentation and shot sampling

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:08:42.622826Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5cbe71b3-35a1-47ab-b07f-abd064bcdac0 · outbound

This paper cites Learning video representations from large lan- guage models.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Learning video representations from large lan- guage models

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:08:42.566586Z

Source-reported events for the cited work

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Observation 79a20398-21bc-4633-ad0f-c8d514f8455c · outbound

This paper cites Learning procedure-aware video represen- tation from instructional videos and their narrations.

ACE: Action Concept Enhancement of Video-Language Models in Procedural Videos Learning procedure-aware video represen- tation from instructional videos and their narrations

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:08:42.457418Z

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