Paper Citation Record · LEDGER

Vid-SME: Membership Inference Attacks against Large Video Understanding Models

As of 21 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 2 inbound Pith citation observations for arXiv:2506.03179.

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

pith.paper-citation-record.v1
2506.03179 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:50:06.708410Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:13:08.790871Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T09:01:26.251127Z

Reference resolution

68 of 68 outbound references displayed

verified exact1
verified fuzzy23
unresolved44
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7f4e4520-4d47-4e6c-9ad3-6aa286caff55 · outbound

This paper cites GPT-4 Technical Report.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

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Observation 3e26e7d7-d90a-4b3a-80c8-4e65fed986f4 · outbound

This paper cites Generalised information and entropy measures in physics.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Generalised information and entropy measures in physics

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:11.806842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 66295b0f-1e58-4b10-b58a-04239842bd7b · outbound

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

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Is space-time attention all you need for video understanding? In ICML, volume 2, page 4, 2021

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:11.552437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ca8023f6-ddb4-4782-8b0d-e3e4b92d85ee · outbound

This paper cites Membership inference attacks from first principles.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Membership inference attacks from first principles

Reference 4

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Source-reported events for the cited work

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Observation 7f7bbade-6c78-49e9-a16b-ea1612f1a136 · outbound

This paper cites The secret sharer: Evaluating and testing unintended memorization in neural networks.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models The secret sharer: Evaluating and testing unintended memorization in neural networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:11.336760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 49d8b062-eec5-49b1-b3d4-dddf34f31380 · outbound

This paper cites Extracting training data from large language models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Extracting training data from large language models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T12:49:59.978144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14d775da-00a6-4a49-9a83-208061a1d3d8 · outbound

This paper cites AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:00.159271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a926d2b-6c4a-42ad-b443-a274a01f0766 · outbound

This paper cites Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:00.355209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c524018-e614-41df-a7c8-69016aedef0b · outbound

This paper cites A hierarchical variational neural uncertainty model for stochastic video prediction.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models A hierarchical variational neural uncertainty model for stochastic video prediction

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:11.122114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 208f3cfc-48b1-4ae0-9f88-27aaada04dd6 · outbound

This paper cites Gan-leaks: A taxonomy of member- ship inference attacks against generative models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Gan-leaks: A taxonomy of member- ship inference attacks against generative models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:10.941307Z

Source-reported events for the cited work

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Observation 9699e74a-8253-45a0-8f46-374a6801760f · outbound

This paper cites Sharegpt4v: Improving large multi-modal models with better captions.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Sharegpt4v: Improving large multi-modal models with better captions

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:00.716534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cdd9a72-425d-4abb-a4b3-13b24ef60617 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:00.824379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a5ec603-2d6f-4143-aae6-6c7838428c5b · outbound

This paper cites A summary on entropy statistics.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models A summary on entropy statistics

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:10.729548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2d7dc7d5-f617-466d-8f08-ff42a8edeb92 · outbound

This paper cites Polynomial expansion for orientation and motion estimation.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Polynomial expansion for orientation and motion estimation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:10.521864Z

Source-reported events for the cited work

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Observation b5ee8706-7825-40c1-ba9c-d76bb39cba8f · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:01.164509Z

Source-reported events for the cited work

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Observation 1891a455-834b-49b7-ab0c-58a0b7554027 · outbound

This paper cites Vision-language models for medical report generation and visual question answering: A review.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Vision-language models for medical report generation and visual question answering: A review

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:01.258821Z

Source-reported events for the cited work

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Observation 22f2957e-5b28-432c-9ea2-ae424f3c9fc6 · outbound

This paper cites LOGAN: Membership Inference Attacks Against Generative Models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models LOGAN: Membership Inference Attacks Against Generative Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:01.377734Z

Source-reported events for the cited work

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Observation c1adcd16-e2b9-4071-9cd5-6a3412f44dcf · outbound

This paper cites Bliva: A simple multimodal llm for better handling of text-rich visual questions.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Bliva: A simple multimodal llm for better handling of text-rich visual questions

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:01.534322Z

Source-reported events for the cited work

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Observation d7f5e69c-d339-41f5-b5cc-32a5d117b1c6 · outbound

This paper cites Membership Inference Attacks Against Vision-Language Models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Membership Inference Attacks Against Vision-Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:01.646953Z

Source-reported events for the cited work

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Observation 1ecb97f7-8d70-47be-b9e0-06a0c996837f · outbound

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

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:01.782739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5affa91c-1097-4287-9971-fc2a790710a4 · outbound

This paper cites VideoChat: Chat-Centric Video Understanding.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models VideoChat: Chat-Centric Video Understanding

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:01.880477Z

Source-reported events for the cited work

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Observation 5da2f132-cbb0-4740-9dc6-055d0af091b1 · outbound

This paper cites Data Lineage Inference: Uncovering Privacy Vulnerabilities of Dataset Pruning.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Data Lineage Inference: Uncovering Privacy Vulnerabilities of Dataset Pruning

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:50:07.109278Z

Source-reported events for the cited work

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Observation d7fcc0d1-d3d9-4499-99ba-d5bf76a85fa0 · outbound

This paper cites Membership inference attacks against large vision-language models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Membership inference attacks against large vision-language models

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15b27c79-583b-4983-9629-be85bee2703c · outbound

This paper cites Next-qa: Next phase of question answering to explaining tem- poral actions.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Next-qa: Next phase of question answering to explaining tem- poral actions

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:10.259861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b411a6af-f3a4-40e2-aef6-bbdf3f5a52a3 · outbound

This paper cites Improved baselines with visual instruction tuning.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Improved baselines with visual instruction tuning

Reference 25

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Source-reported events for the cited work

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Observation ecb9d7da-ac86-42c7-b9aa-2e9c4884b68c · outbound

This paper cites Llava-next: Improved reasoning, ocr, and world knowledge, January 2024.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Llava-next: Improved reasoning, ocr, and world knowledge, January 2024

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:02.525025Z

Source-reported events for the cited work

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Observation c79afcb2-883b-4e35-98be-2d25af95dbe6 · outbound

This paper cites St-llm: Large language models are effective temporal learners.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models St-llm: Large language models are effective temporal learners

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:10.065850Z

Source-reported events for the cited work

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Observation a2044a25-f7d4-4fb3-9665-8c2f0ab4490f · outbound

This paper cites TempCompass: Do Video LLMs Really Understand Videos?.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models TempCompass: Do Video LLMs Really Understand Videos?

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:02.767971Z

Source-reported events for the cited work

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Observation a0e8be73-74c8-40ed-ac7e-74a5cf6f213b · outbound

This paper cites VideoEval-Pro: Robust and Realistic Long Video Understanding Evaluation.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models VideoEval-Pro: Robust and Realistic Long Video Understanding Evaluation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:02.846860Z

Source-reported events for the cited work

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Observation a5ebe86a-f4aa-45d0-8029-110c21ad2e9d · outbound

This paper cites Membership Inference on Word Embedding and Beyond.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Membership Inference on Word Embedding and Beyond

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:02.921582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bca8670-5e05-4c3b-8560-fd380795588a · outbound

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

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:02.944973Z

Source-reported events for the cited work

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Observation 101ecbd6-fda6-4c6b-975c-f434139abf21 · outbound

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

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Expanding language-image pretrained models for general video recognition

Reference 33

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Source-reported events for the cited work

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Observation 5be1f143-d460-424e-adde-14d4427f23cf · outbound

This paper cites Slowfocus: Enhancing fine-grained temporal understanding in video llm.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Slowfocus: Enhancing fine-grained temporal understanding in video llm

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:09.857404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fd8a5bad-f8e3-47bf-bab1-f11070dce1b4 · outbound

This paper cites Learning latent subevents in activity videos using temporal attention filters.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Learning latent subevents in activity videos using temporal attention filters

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:09.666613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 190b3730-464f-4765-aa75-27356f97060b · outbound

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

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Fine-tuned clip models are efficient video learners

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:09.475271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b5a9eed2-063f-4369-83c6-f8cdb5c0e94f · outbound

This paper cites CinePile: A Long Video Question Answering Dataset and Benchmark.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models CinePile: A Long Video Question Answering Dataset and Benchmark

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:03.465772Z

Source-reported events for the cited work

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Observation 26932e13-46af-4771-9da3-cfb109305d63 · outbound

This paper cites On measures of entropy and information.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models On measures of entropy and information

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:09.290443Z

Source-reported events for the cited work

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Observation 705e65bc-7f65-4da8-87d8-0dc7e92d5a44 · outbound

This paper cites ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:03.631859Z

Source-reported events for the cited work

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Observation be25302d-63d5-4bc9-b342-40a1639baf46 · outbound

This paper cites LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs

Reference 40

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Source-reported events for the cited work

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Observation 3a116c7b-1442-465e-b999-c4128a17f05a · outbound

This paper cites A mathematical theory of communication.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models A mathematical theory of communication

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:03.803803Z

Source-reported events for the cited work

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Observation 1e88c572-da1e-4a96-a1b2-e0fade9e3c6a · outbound

This paper cites New non-additive measures of entropy for discrete probability distributions.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models New non-additive measures of entropy for discrete probability distributions

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:09.105033Z

Source-reported events for the cited work

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Observation aa40c5ee-0017-46be-99b5-092d1aa6f33f · outbound

This paper cites Detecting Pretraining Data from Large Language Models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Detecting Pretraining Data from Large Language Models

Reference 43

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Source-reported events for the cited work

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Observation 0b9a2264-292f-44ec-a314-324191e1cc0b · outbound

This paper cites Membership inference attacks against machine learning models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Membership inference attacks against machine learning models

Reference 44

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Observation 4573f7fc-2348-47f0-8f17-e32ee76a36e2 · outbound

This paper cites Visual Text Processing: A Comprehensive Review and Unified Evaluation.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Visual Text Processing: A Comprehensive Review and Unified Evaluation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:04.127536Z

Source-reported events for the cited work

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Observation c8017646-7848-455d-855d-be4096fd1aca · outbound

This paper cites Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:04.246155Z

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Observation 2e2d68cb-e4c0-4007-957b-597d2bcba0a6 · outbound

This paper cites Two-stream convolutional networks for action recognition in videos.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Two-stream convolutional networks for action recognition in videos

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:04.343404Z

Source-reported events for the cited work

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Observation 3e1c3333-340c-46ec-8aeb-59f5639704b8 · outbound

This paper cites Information leakage in embedding models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Information leakage in embedding models

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:08.940596Z

Source-reported events for the cited work

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Observation 6e2ae5dc-8272-44cb-9f75-837c48bf77bb · outbound

This paper cites Machine learning models that remember too much.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Machine learning models that remember too much

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T12:50:04.581764Z

Source-reported events for the cited work

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Observation af2f5f85-d54b-4bb6-b43f-8c0e8f3bef2d · outbound

This paper cites Systematic evaluation of privacy risks of machine learning models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Systematic evaluation of privacy risks of machine learning models

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:08.767703Z

Source-reported events for the cited work

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Observation f186be7a-2ab3-4ac5-8313-7f69beb88b20 · outbound

This paper cites Membership inference attacks against adversari- ally robust deep learning models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Membership inference attacks against adversari- ally robust deep learning models

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:08.568425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6e6be34f-de80-4c2f-8990-3be96fac9342 · outbound

This paper cites On generalized information measures and their applications.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models On generalized information measures and their applications

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:08.338855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5d3dac5a-6b4e-497b-95e5-5ecde0569248 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 53

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Observation a55d195b-e3c1-4842-a420-b368c67e69e8 · outbound

This paper cites Possible generalization of boltzmann-gibbs statistics.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Possible generalization of boltzmann-gibbs statistics

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:08.185744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e75b7c71-5106-4d83-bd6f-afcb7403748e · outbound

This paper cites Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Approximate Unlearning Completeness.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Approximate Unlearning Completeness

Reference 55

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Reference 56

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Vid-SME: Membership Inference Attacks against Large Video Understanding Models Videoagent: Long-form video understanding with large language model as agent

Reference 57

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Observation 0ec80a0b-0802-449e-965a-9f21b2726c38 · outbound

This paper cites Membership Inference Attacks on Large-Scale Models: A Survey.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Membership Inference Attacks on Large-Scale Models: A Survey

Reference 58

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Vid-SME: Membership Inference Attacks against Large Video Understanding Models Optimizing video prediction via video frame interpola- tion

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:50:07.662811Z

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Observation 7fd37cb5-b0a3-42f1-83bc-ce00b0bbe0f2 · outbound

This paper cites Privacy risk in machine learning: Analyzing the connection to overfitting.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Privacy risk in machine learning: Analyzing the connection to overfitting

Reference 60

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Vid-SME: Membership Inference Attacks against Large Video Understanding Models Memory-enhanced Retrieval Augmentation for Long Video Understanding

Reference 61

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Vid-SME: Membership Inference Attacks against Large Video Understanding Models Low-Cost High-Power Membership Inference Attacks

Reference 62

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Vid-SME: Membership Inference Attacks against Large Video Understanding Models Understanding deep learning (still) requires rethinking generalization

Reference 63

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Observation 548de2d1-4350-4c21-b212-3e1c67f612a8 · outbound

This paper cites Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models

Reference 64

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Vid-SME: Membership Inference Attacks against Large Video Understanding Models Long Context Transfer from Language to Vision

Reference 65

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Vid-SME: Membership Inference Attacks against Large Video Understanding Models Instruction tuning for large language models: A survey

Reference 66

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Observation 34b4344b-0985-4f43-8c09-eb8538e5b39d · outbound

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Vid-SME: Membership Inference Attacks against Large Video Understanding Models Llava-next: A strong zero-shot video understanding model, April 2024

Reference 67

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Observation f2ccfd2b-e414-47d7-a3be-620b054f5142 · outbound

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Vid-SME: Membership Inference Attacks against Large Video Understanding Models MLVU: Benchmarking Multi-task Long Video Understanding

Reference 68

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Observation 0bcd2431-6ade-4903-811b-cce29a24883d · outbound

This paper cites A survey on deep learning technique for video segmentation.

Vid-SME: Membership Inference Attacks against Large Video Understanding Models A survey on deep learning technique for video segmentation

Reference 69

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Pith citing papers

Observation cde2b3d5-766a-4eb8-98d8-c27cdfbdd032 · inbound

Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification cites this paper.

Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification Vid-SME: Membership Inference Attacks against Large Video Understanding Models

Reference 29

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Observation 113347f8-e615-4b6b-879c-4c4c2cd4cb73 · inbound

Membership Inference Attacks Against Video Large Language Models cites this paper.

Membership Inference Attacks Against Video Large Language Models Vid-SME: Membership Inference Attacks against Large Video Understanding Models

Reference 22

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