Towards Long Video Understanding via Fine-detailed Video Story Generation | Paper Citation Record

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This paper cites Intermediary-guided bidi- rectional spatial-temporal aggregation network for video-based visible- infrared person re-identification,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Intermediary-guided bidi- rectional spatial-temporal aggregation network for video-based visible- infrared person re-identification,

Reference 1

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Observation 03b84715-37a0-4f07-9597-baef3232868b · outbound

This paper cites Video moment re- trieval via comprehensive relation-aware network,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Video moment re- trieval via comprehensive relation-aware network,

Reference 2

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Observation 3c3e072d-7723-4ee6-b14c-14fd0680d94e · outbound

This paper cites Self-supervised adversarial video summarizer with context latent sequence learning,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Self-supervised adversarial video summarizer with context latent sequence learning,

Reference 3

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Observation 2c88bb87-0543-4ad9-8de1-7925763f3a63 · outbound

This paper cites Complementarity- aware space learning for video-text retrieval,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Complementarity- aware space learning for video-text retrieval,

Reference 4

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Observation 157f858f-1c4c-4644-9cf2-07453d74dfcb · outbound

This paper cites Moma-lrg: Language-refined graphs for multi-object multi-actor activity parsing,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Moma-lrg: Language-refined graphs for multi-object multi-actor activity parsing,

Reference 5

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Observation 3c5484a6-9cf2-4b62-8e17-7f1bf7c1b273 · outbound

This paper cites Videoclip: Contrastive pre- training for zero-shot video-text understanding,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Videoclip: Contrastive pre- training for zero-shot video-text understanding,

Reference 6

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Observation 6ddc86b7-04cf-4c20-a1b1-d33e8b7c07ea · outbound

This paper cites Graph convolutional module for temporal action localization in videos,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Graph convolutional module for temporal action localization in videos,

Reference 7

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Observation 304fefc4-3b33-4afd-a4bb-1de82d73b17c · outbound

This paper cites Evcap: Element- aware video captioning,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Evcap: Element- aware video captioning,

Reference 8

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Observation 246b13d7-365c-4a74-bc4c-c0679c3f3802 · outbound

This paper cites Multi-granularity interaction and integration network for video question answering,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Multi-granularity interaction and integration network for video question answering,

Reference 9

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Observation 106cebde-0324-45a0-808f-ff7265d0a44d · outbound

This paper cites Video question answering with semantic disentanglement and reasoning,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Video question answering with semantic disentanglement and reasoning,

Reference 10

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Observation 548d2b2a-2e8e-473e-85f3-74925b113941 · outbound

This paper cites Multilevel semantic interaction alignment for video–text cross-modal retrieval,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Multilevel semantic interaction alignment for video–text cross-modal retrieval,

Reference 11

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Observation 37202589-7b99-4879-8fac-b0d933076c10 · outbound

This paper cites VideoChat: Chat-Centric Video Understanding.

Towards Long Video Understanding via Fine-detailed Video Story Generation VideoChat: Chat-Centric Video Understanding

Reference 12

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Observation bc909dc9-ba3a-4750-bbe9-39769e529306 · outbound

This paper cites Video-llama: An instruction-tuned audio-visual language model for video understanding,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Video-llama: An instruction-tuned audio-visual language model for video understanding,

Reference 13

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Observation f77b4e5e-7d18-4849-a028-b1c48563771f · outbound

This paper cites MovieChat: From Dense Token to Sparse Memory for Long Video Understanding.

Towards Long Video Understanding via Fine-detailed Video Story Generation MovieChat: From Dense Token to Sparse Memory for Long Video Understanding

Reference 14

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Observation 831d8942-a346-4f40-9a3b-25cb57a1004c · outbound

This paper cites Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models.

Towards Long Video Understanding via Fine-detailed Video Story Generation Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models

Reference 15

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Observation 89fee407-103d-46cb-831e-8e19fb6d605f · outbound

This paper cites Language models with image descriptors are strong few-shot video-language learners,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Language models with image descriptors are strong few-shot video-language learners,

Reference 16

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Observation 68e75ac0-42de-4cbc-8e57-69a8d3917f5a · outbound

This paper cites Compressed video action recognition with dual-stream and dual-modal transformer,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Compressed video action recognition with dual-stream and dual-modal transformer,

Reference 17

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This paper cites Dynamic spatial focus for efficient compressed video action recognition,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Dynamic spatial focus for efficient compressed video action recognition,

Reference 18

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Observation 5f1d5e46-a24d-44ee-88fa-eee4f7a9d064 · outbound

This paper cites Alignment-guided temporal atten- tion for video action recognition,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Alignment-guided temporal atten- tion for video action recognition,

Reference 19

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Observation 787aab86-06d4-43a0-befd-c74f18c3aa3b · outbound

This paper cites Slowfast networks for video recognition,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Slowfast networks for video recognition,

Reference 20

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Observation 2071a66f-0e0e-4850-9335-33bc33a806d5 · outbound

This paper cites Temporal distinct representation learning for action recognition,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Temporal distinct representation learning for action recognition,

Reference 21

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Observation 3d99e65b-f375-4487-aafe-5d7a2e96741b · outbound

This paper cites Truncate-split-contrast: a framework for learning from mislabeled videos,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Truncate-split-contrast: a framework for learning from mislabeled videos,

Reference 22

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Observation de6591e7-2ab0-41c1-a586-ed130cdf71c1 · outbound

This paper cites Reading-strategy inspired visual representation learning for text-to- video retrieval,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Reading-strategy inspired visual representation learning for text-to- video retrieval,

Reference 23

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Observation 903fe238-f9d2-46cb-89ec-7c40649e1aff · outbound

This paper cites Use what you have: Video retrieval using representations from collaborative experts,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Use what you have: Video retrieval using representations from collaborative experts,

Reference 24

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This paper cites Dual encoding for zero-example video retrieval,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Dual encoding for zero-example video retrieval,

Reference 25

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Observation 61a2a580-296b-4df4-bf20-aff3036720a2 · outbound

This paper cites Locvtp: Video-text pre-training for temporal localization,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Locvtp: Video-text pre-training for temporal localization,

Reference 26

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Observation adad5951-16a8-4bfb-83c9-20e48977a0a0 · outbound

This paper cites Breaking winner-takes-all: Iterative-winners-out networks for weakly supervised temporal action localization,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Breaking winner-takes-all: Iterative-winners-out networks for weakly supervised temporal action localization,

Reference 27

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Observation 8c562c82-db62-4be2-bd76-c3c12052f130 · outbound

This paper cites Cross time-frequency transformer for temporal action localization,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Cross time-frequency transformer for temporal action localization,

Reference 28

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This paper cites Slow motion matters: A slow motion enhanced network for weakly supervised temporal action localization,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Slow motion matters: A slow motion enhanced network for weakly supervised temporal action localization,

Reference 29

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This paper cites Long-form video- language pre-training with multimodal temporal contrastive learning,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Long-form video- language pre-training with multimodal temporal contrastive learning,

Reference 30

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Observation 4320506b-7c55-417b-ad3d-d9a5b657c202 · outbound

This paper cites VideoGraph: Recognizing Minutes-Long Human Activities in Videos.

Towards Long Video Understanding via Fine-detailed Video Story Generation VideoGraph: Recognizing Minutes-Long Human Activities in Videos

Reference 31

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Observation be66552c-aac9-465d-a353-7201b08941d3 · outbound

This paper cites Supervoxel attention graphs for long-range video modeling,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Supervoxel attention graphs for long-range video modeling,

Reference 32

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Observation 0c772c00-a4df-49fe-a93a-02cc99cf828f · outbound

This paper cites Long movie clip classification with state-space video models,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Long movie clip classification with state-space video models,

Reference 33

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This paper cites S4nd: Modeling images and videos as multidimensional signals with state spaces,.

Towards Long Video Understanding via Fine-detailed Video Story Generation S4nd: Modeling images and videos as multidimensional signals with state spaces,

Reference 34

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This paper cites Selective structured state-spaces for long-form video understanding,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Selective structured state-spaces for long-form video understanding,

Reference 35

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This paper cites Efficiently modeling long sequences with structured state spaces,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Efficiently modeling long sequences with structured state spaces,

Reference 36

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This paper cites Mgsampler: An explainable sampling strategy for video action recognition,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Mgsampler: An explainable sampling strategy for video action recognition,

Reference 37

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This paper cites Adaframe: Adaptive frame selection for fast video recognition,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Adaframe: Adaptive frame selection for fast video recognition,

Reference 38

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This paper cites Localizing moments in long video via multimodal guidance,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Localizing moments in long video via multimodal guidance,

Reference 39

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Observation 00a45254-eb61-4d1d-bec5-d4f60dcc6e25 · outbound

This paper cites Mad: A scalable dataset for language grounding in videos from movie audio descriptions,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Mad: A scalable dataset for language grounding in videos from movie audio descriptions,

Reference 40

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This paper cites End-to-end learning of visual representations from uncurated instructional videos,.

Towards Long Video Understanding via Fine-detailed Video Story Generation End-to-end learning of visual representations from uncurated instructional videos,

Reference 41

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Observation bf90c54e-8f4c-4c1e-81b9-45c03751ff83 · outbound

This paper cites Merlot: Multimodal neural script knowledge models,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Merlot: Multimodal neural script knowledge models,

Reference 42

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Observation 8a745a5d-ad95-4236-9c48-2f872ed5b492 · outbound

This paper cites Scaling up vision-language pre-training for image captioning,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Scaling up vision-language pre-training for image captioning,

Reference 43

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This paper cites Gbc: Guided alignment and adaptive boosting clip bridging vision and language for robust action recognition,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Gbc: Guided alignment and adaptive boosting clip bridging vision and language for robust action recognition,

Reference 44

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This paper cites Unsu- pervised pre-training for temporal action localization tasks,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Unsu- pervised pre-training for temporal action localization tasks,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.409107Z

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This paper cites Clip4clip: An empirical study of CLIP for end to end video clip retrieval and captioning,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Clip4clip: An empirical study of CLIP for end to end video clip retrieval and captioning,

Reference 46

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Observation 7d6a0576-d691-432a-9b02-92d48310de48 · outbound

This paper cites Human action recognition and prediction: A survey,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Human action recognition and prediction: A survey,

Reference 47

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This paper cites A survey on video-based human action recognition: recent updates, datasets, challenges, and applications,.

Towards Long Video Understanding via Fine-detailed Video Story Generation A survey on video-based human action recognition: recent updates, datasets, challenges, and applications,

Reference 48

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This paper cites Lavender: Unifying video-language understanding as masked lan- guage modeling,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Lavender: Unifying video-language understanding as masked lan- guage modeling,

Reference 49

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

Towards Long Video Understanding via Fine-detailed Video Story Generation Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre- training,

Reference 50

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This paper cites Videomae v2: Scaling video masked autoencoders with dual masking,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Videomae v2: Scaling video masked autoencoders with dual masking,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.347902Z

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This paper cites VIOLET : End-to-End Video-Language Transformers with Masked Visual-token Modeling.

Towards Long Video Understanding via Fine-detailed Video Story Generation VIOLET : End-to-End Video-Language Transformers with Masked Visual-token Modeling

Reference 52

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This paper cites All in one: Exploring unified video-language pre-training,.

Towards Long Video Understanding via Fine-detailed Video Story Generation All in one: Exploring unified video-language pre-training,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.336103Z

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Observation 69b91bbb-8d7a-4fc6-9e55-b0d424f983e9 · outbound

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

Towards Long Video Understanding via Fine-detailed Video Story Generation InternVideo: General Video Foundation Models via Generative and Discriminative Learning

Reference 54

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This paper cites Language mod- els are few-shot learners,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Language mod- els are few-shot learners,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.325979Z

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This paper cites GLM: general language model pretraining with autoregressive blank infilling,.

Towards Long Video Understanding via Fine-detailed Video Story Generation GLM: general language model pretraining with autoregressive blank infilling,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.315557Z

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Observation c8db19b9-f461-438d-9453-3f5b81894773 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Towards Long Video Understanding via Fine-detailed Video Story Generation LLaMA: Open and Efficient Foundation Language Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T19:59:13.483476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b41f2851-7240-4be8-bf5a-73bca0b77d97 · outbound

This paper cites MIST : Multi-modal iterative spatial-temporal transformer for long-form video question answering,.

Towards Long Video Understanding via Fine-detailed Video Story Generation MIST : Multi-modal iterative spatial-temporal transformer for long-form video question answering,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.303595Z

Source-reported events for the cited work

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Observation cd159143-971a-4beb-bada-fac3eb9a60c5 · outbound

This paper cites A joint sequence fusion model for video question answering and retrieval,.

Towards Long Video Understanding via Fine-detailed Video Story Generation A joint sequence fusion model for video question answering and retrieval,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.291561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d2387de6-656c-40f1-ab0f-432ba582b063 · outbound

This paper cites Video question answering via gradually refined attention over appear- ance and motion,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Video question answering via gradually refined attention over appear- ance and motion,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.279595Z

Source-reported events for the cited work

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Observation bff493ec-b099-46b2-b64f-2e3d8539f224 · outbound

This paper cites Activitynet-qa: A dataset for understanding complex web videos via question answering,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Activitynet-qa: A dataset for understanding complex web videos via question answering,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.268566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 522cb6ed-6d9f-4a78-8400-76f8bf6ab18e · outbound

This paper cites Swinbert: End-to-end transformers with sparse attention for video captioning,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Swinbert: End-to-end transformers with sparse attention for video captioning,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.256936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 08ad18dd-0240-4738-ae53-f7bf796daec9 · outbound

This paper cites Vid2seq: Large-scale pretraining of a visual language model for dense video captioning,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Vid2seq: Large-scale pretraining of a visual language model for dense video captioning,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.245299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7cadfdc3-52c4-4d92-8868-78f9cb26701b · outbound

This paper cites Dense- captioning events in videos,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Dense- captioning events in videos,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.233671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation df2e5754-c242-4eb4-9377-621b106bdf0f · outbound

This paper cites BLIP-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,.

Towards Long Video Understanding via Fine-detailed Video Story Generation BLIP-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.221672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0f9707f9-ad5b-47f5-9be7-fc6146ad7ac3 · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

Towards Long Video Understanding via Fine-detailed Video Story Generation MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-11T19:59:13.512195Z

Source-reported events for the cited work

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Observation 447ac7d9-1ccd-48aa-8c0b-d5ab82159b1f · outbound

This paper cites InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation.

Towards Long Video Understanding via Fine-detailed Video Story Generation InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-11T19:59:13.516220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebac29eb-40df-406a-84f7-88fdeb1499aa · outbound

This paper cites Pyscenedetect,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Pyscenedetect,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.209964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4b1ddd92-00f5-44b7-9f41-36cc95970907 · outbound

This paper cites Decord: An efficient video loader for deep learning,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Decord: An efficient video loader for deep learning,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.197450Z

Source-reported events for the cited work

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Observation f11bf45d-6f12-488f-b4fd-81bd7de680d8 · outbound

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

Towards Long Video Understanding via Fine-detailed Video Story Generation Learning transferable visual models from natural language supervision,

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T19:59:13.525872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5849239-8def-49a6-a4c3-cd867a0ed0b8 · outbound

This paper cites DINO: DETR with improved denoising anchor boxes for end-to-end object detection,.

Towards Long Video Understanding via Fine-detailed Video Story Generation DINO: DETR with improved denoising anchor boxes for end-to-end object detection,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.179339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ee5186e6-8829-4917-80a0-799e771344e1 · outbound

This paper cites Sentence-bert: Sentence embeddings using siamese bert-networks,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Sentence-bert: Sentence embeddings using siamese bert-networks,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.168721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 11655f67-fe3d-4ae2-a455-a70c149ca17b · outbound

This paper cites Partially relevant video retrieval,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Partially relevant video retrieval,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.158363Z

Source-reported events for the cited work

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Observation 5a466a5f-d901-4c80-88a4-acaad7416c99 · outbound

This paper cites Joint searching and grounding: Multi-granularity video content retrieval,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Joint searching and grounding: Multi-granularity video content retrieval,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.147009Z

Source-reported events for the cited work

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Observation bef96942-deb3-4b17-ad8e-b537412a17ba · outbound

This paper cites Hit: Hierar- chical transformer with momentum contrast for video-text retrieval,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Hit: Hierar- chical transformer with momentum contrast for video-text retrieval,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.136686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 619faa62-256d-4b58-b41f-2d23bc20fbff · outbound

This paper cites Multi-modal trans- former for video retrieval,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Multi-modal trans- former for video retrieval,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.126362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 818e37cf-5c0d-4737-b57a-81c6e1766cc0 · outbound

This paper cites Cross-modal and hierarchical modeling of video and text,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Cross-modal and hierarchical modeling of video and text,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.115696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 05a59bbb-5df8-486d-91ba-046535002610 · outbound

This paper cites Eclipse: Efficient long- range video retrieval using sight and sound,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Eclipse: Efficient long- range video retrieval using sight and sound,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.105621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7750a39d-77a5-481a-9aa4-1712f209efa4 · outbound

This paper cites TALL: temporal activity localization via language query,.

Towards Long Video Understanding via Fine-detailed Video Story Generation TALL: temporal activity localization via language query,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.095823Z

Source-reported events for the cited work

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Observation f586d4ae-e6cc-47e5-8c52-ee0c3c2a2acb · outbound

This paper cites Hollywood in homes: Crowdsourcing data collection for activity understanding,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Hollywood in homes: Crowdsourcing data collection for activity understanding,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.085989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2c271b89-00d5-48d8-ad34-618c428d11a8 · outbound

This paper cites MSR-VTT: A large video descrip- tion dataset for bridging video and language,.

Towards Long Video Understanding via Fine-detailed Video Story Generation MSR-VTT: A large video descrip- tion dataset for bridging video and language,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.076134Z

Source-reported events for the cited work

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Observation f42f821b-3b50-472a-875e-c61b44477382 · outbound

This paper cites Question generation via overgenerating transformations and ranking,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Question generation via overgenerating transformations and ranking,

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.065916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b12f594c-664e-4e6a-b75c-8f8707ec5244 · outbound

This paper cites Egoschema: A diagnostic benchmark for very long-form video language understanding,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Egoschema: A diagnostic benchmark for very long-form video language understanding,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.056879Z

Source-reported events for the cited work

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Observation 4a7c3694-66ff-4de1-bb2f-002d1f1b1d72 · outbound

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

Towards Long Video Understanding via Fine-detailed Video Story Generation Ego4d: Around the world in 3, 000 hours of egocentric video,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.047172Z

Source-reported events for the cited work

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Observation 884ac27b-36fd-4ab8-9bcd-0063a955b8f8 · outbound

This paper cites Next-qa: Next phase of question-answering to explaining temporal actions,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Next-qa: Next phase of question-answering to explaining temporal actions,

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.036272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 22780f74-4a8e-43b9-8b2e-19825e63da4e · outbound

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

Towards Long Video Understanding via Fine-detailed Video Story Generation Quo vadis, action recognition? a new model and the kinetics dataset,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.026777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation de50226d-8903-4b14-bd41-818fd009af55 · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Towards Long Video Understanding via Fine-detailed Video Story Generation Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-11T19:59:13.578033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b77bdc2-774f-4302-b3fb-3a29b29d2bd5 · outbound

This paper cites Sharegpt: Share your wildest chatgpt conversations with one click,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Sharegpt: Share your wildest chatgpt conversations with one click,

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.017304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4e65467a-9dc8-4212-b7e0-f05e6b940993 · outbound

This paper cites AnglE-optimized Text Embeddings.

Towards Long Video Understanding via Fine-detailed Video Story Generation AnglE-optimized Text Embeddings

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-11T19:59:13.585145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7be46fc4-02ac-4d22-af5d-02c447adc113 · outbound

This paper cites Video corpus moment retrieval with contrastive learning,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Video corpus moment retrieval with contrastive learning,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:14.007278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8875e9a0-e7ed-4f2b-9067-a3ebc767d51c · outbound

This paper cites TVR: A large-scale dataset for video-subtitle moment retrieval,.

Towards Long Video Understanding via Fine-detailed Video Story Generation TVR: A large-scale dataset for video-subtitle moment retrieval,

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:13.997127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3aeba3ae-12b5-4ea8-96d3-233932ff55b5 · outbound

This paper cites Dual learning with dynamic knowledge distillation for partially relevant video retrieval,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Dual learning with dynamic knowledge distillation for partially relevant video retrieval,

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:13.986868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f92a385a-4186-4f2f-af3c-81ae0c0f3a94 · outbound

This paper cites Video-LLaVA: Learning United Visual Representation by Alignment Before Projection.

Towards Long Video Understanding via Fine-detailed Video Story Generation Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-11T19:59:13.597852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab79c81a-42d1-4f97-aa46-be999033b701 · outbound

This paper cites Just ask: Learning to answer questions from millions of narrated videos,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Just ask: Learning to answer questions from millions of narrated videos,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:13.976799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2528ebbc-87f5-4143-8735-33589eb2ea56 · outbound

This paper cites MERLOT RESERVE: neural script knowledge through vision and language and sound,.

Towards Long Video Understanding via Fine-detailed Video Story Generation MERLOT RESERVE: neural script knowledge through vision and language and sound,

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:13.965769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cf7169bb-7386-4afe-a9d6-dd790f1767c7 · outbound

This paper cites Zero-shot video question answering via frozen bidirectional language models,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Zero-shot video question answering via frozen bidirectional language models,

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:13.955780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 921d8ba2-5ff9-4525-8263-44a3a5f22613 · outbound

This paper cites Hitea: Hierarchical temporal-aware video-language pre-training,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Hitea: Hierarchical temporal-aware video-language pre-training,

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:13.944568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0e4515bd-6b0e-47f2-80a4-eff5f7432f4b · outbound

This paper cites Self-chained image-language model for video localization and question answering,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Self-chained image-language model for video localization and question answering,

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:13.933048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 22431014-9daa-4649-902f-4214ea607eb1 · outbound

This paper cites Memory consolidation enables long-context video understanding,.

Towards Long Video Understanding via Fine-detailed Video Story Generation Memory consolidation enables long-context video understanding,

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:59:13.922071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8f5f7710-bbd0-4204-ab66-f4012eaf31af · outbound

This paper cites mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality.

Towards Long Video Understanding via Fine-detailed Video Story Generation mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-11T19:59:13.619204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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