Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:27:00.996471Z
Paper Citation Record · LEDGER
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation
As of 18 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 1 inbound Pith citation observation for arXiv:2505.15233.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-20T15:08:25.309094Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T15:13:25.040118Z
Reference resolution
74 of 74 outbound references displayed
- verified exact2
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- unresolved19
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation bb4cd9f1-cff9-435c-89b3-9c71e68d3766 · outbound
This paper cites Mesonet: a compact facial video forgery detection network.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Mesonet: a compact facial video forgery detection network
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c58e74d7-cdc7-43a4-8e66-492732a5fe8c · outbound
This paper cites A review of modern audio deepfake detection methods: challenges and future directions.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation A review of modern audio deepfake detection methods: challenges and future directions
Reference 2
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1f187ee3-29bd-4605-9309-632285bf018e · outbound
This paper cites Do you really mean that? content driven audio-visual deepfake dataset and multimodal method for temporal forgery localization.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Do you really mean that? content driven audio-visual deepfake dataset and multimodal method for temporal forgery localization
Reference 3
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation fe38a54f-d59a-4ce4-8404-a8aa568b0c69 · outbound
This paper cites Quo vadis, action recognition? a new model and the kinetics dataset.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Quo vadis, action recognition? a new model and the kinetics dataset
Reference 4
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6ce7981-1a59-44ce-bea4-20bcf51e17cb · outbound
This paper cites an unresolved cited work.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Unresolved cited work
Reference 5
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 933e19fd-3ba1-4275-9383-5013726f029d · outbound
This paper cites Self-supervised learning of adversarial example: Towards good generalizations for deepfake detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Self-supervised learning of adversarial example: Towards good generalizations for deepfake detection
Reference 6
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 32a37ffa-7e7c-4397-b206-ab43e5cbd069 · outbound
This paper cites A Simple Framework for Contrastive Learning of Visual Representations.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation A Simple Framework for Contrastive Learning of Visual Representations
Reference 7
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 50ac14fd-fba5-4306-a83f-f50b062b16be · outbound
This paper cites Exploring simple siamese representation learning.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Exploring simple siamese representation learning
Reference 8
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a8f0832a-cbc0-436c-8860-320875445262 · outbound
This paper cites Sophia Koepke, Ying Shan, and Zeynep Akata.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Sophia Koepke, Ying Shan, and Zeynep Akata
Reference 9
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 64487f5f-8e60-4cc6-bc87-df0abcfee9a4 · outbound
This paper cites V oice-face homogeneity tells deepfake.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation V oice-face homogeneity tells deepfake
Reference 10
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5769a50b-9188-4a15-8163-a547698489f2 · outbound
This paper cites Can We Leave Deepfake Data Behind in Training Deepfake Detector?.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Can We Leave Deepfake Data Behind in Training Deepfake Detector?
Reference 11
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 129e1880-4817-4737-ae70-a38b7652923e · outbound
This paper cites Xception: Deep learning with depthwise separable convolutions.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Xception: Deep learning with depthwise separable convolutions
Reference 12
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8284eb72-ad9e-472d-a7aa-63f5969c98d0 · outbound
This paper cites Not made for each other- audio-visual dissonance-based deepfake detection and localization.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Not made for each other- audio-visual dissonance-based deepfake detection and localization
Reference 13
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 56d9c05b-5efd-4049-9806-edda9d0c0262 · outbound
This paper cites Audio-visual person-of-interest deepfake detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Audio-visual person-of-interest deepfake detection
Reference 14
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5eb7d261-3663-4989-872a-9a2da6120e54 · outbound
This paper cites Dong, Jin Wang, Renhe Ji, Jiajun Liang, Haoqiang Fan, and Zheng Ge.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Dong, Jin Wang, Renhe Ji, Jiajun Liang, Haoqiang Fan, and Zheng Ge
Reference 15
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5b2b32de-9a52-488c-848a-68dffb596ebb · outbound
This paper cites www.github.com/MarekKowalski/FaceSwap Accessed 2021-04-24.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation www.github.com/MarekKowalski/FaceSwap Accessed 2021-04-24
Reference 16
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 85c18813-1f05-4efb-ba7f-1188277e5ec9 · outbound
This paper cites Self-supervised video forensics by audio-visual anomaly detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Self-supervised video forensics by audio-visual anomaly detection
Reference 17
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2a551dd0-faf3-411d-88b2-5fbe681f7e98 · outbound
This paper cites Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
Reference 18
- Resolution
- verified exact
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Source-reported events for the cited work
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Observation 910b8953-1a46-46c7-80d4-6a8afc3b5515 · outbound
This paper cites Imagebind one embedding space to bind them all.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Imagebind one embedding space to bind them all
Reference 19
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1d42e731-48c8-4c7c-adb2-ceddac4857b8 · outbound
This paper cites Leveraging real talking faces via self-supervision for robust forgery detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Leveraging real talking faces via self-supervision for robust forgery detection
Reference 20
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 242ef530-74f6-4b75-955b-c98b0fde5954 · outbound
This paper cites Lips don’t lie: A generalisable and robust approach to face forgery detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Lips don’t lie: A generalisable and robust approach to face forgery detection
Reference 21
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 459ebd5f-63b3-4792-9178-d88286def08e · outbound
This paper cites Masked autoencoders are scalable vision learners.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Masked autoencoders are scalable vision learners
Reference 22
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c7900e5d-7aea-49b9-9312-8e74246eb0b9 · outbound
This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen
Reference 23
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 105c5295-9d6b-4502-bb53-817ee1220e08 · outbound
This paper cites Lora: Low-rank adaptation of large language models.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Lora: Low-rank adaptation of large language models
Reference 24
- Resolution
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Source-reported events for the cited work
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Observation 02a2a4a0-ad58-4f6e-846c-7aec0d9ea89c · outbound
This paper cites Avfakenet: A unified end-to-end dense swin transformer deep learning model for audio-visual deepfakes detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Avfakenet: A unified end-to-end dense swin transformer deep learning model for audio-visual deepfakes detection
Reference 25
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4c94acf6-c13d-49e4-b28c-c07b57924b0c · outbound
This paper cites Information theory and statistical mechanics.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Information theory and statistical mechanics
Reference 26
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ceb33f51-45cd-4bcf-8c1c-5be15e06db80 · outbound
This paper cites an unresolved cited work.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Unresolved cited work
Reference 27
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6a14a426-5563-4cd0-8978-90fd0c27ee70 · outbound
This paper cites FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset
Reference 28
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aed45079-acd6-41b8-a7b5-9021e513db61 · outbound
This paper cites Fast face-swap using convolu- tional neural networks.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Fast face-swap using convolu- tional neural networks
Reference 29
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9a0605a9-493f-4e9d-8144-64663846db63 · outbound
This paper cites Face x-ray for more general face forgery detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Face x-ray for more general face forgery detection
Reference 30
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 15b3d7be-6001-44bf-b67b-a03298ab009d · outbound
This paper cites A Survey on Speech Deepfake Detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation A Survey on Speech Deepfake Detection
Reference 31
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a63c7869-feb6-493e-b625-b0cb81abfd36 · outbound
This paper cites Celeb-df: A large-scale challenging dataset for deepfake forensics.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Celeb-df: A large-scale challenging dataset for deepfake forensics
Reference 32
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 22291b3e-f02a-49b8-9700-1ad0cdd5a626 · outbound
This paper cites Lips are lying: Spotting the temporal inconsistency between audio and visual in lip-syncing deepfakes.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Lips are lying: Spotting the temporal inconsistency between audio and visual in lip-syncing deepfakes
Reference 33
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b27d098b-b827-4513-b161-e801418e734b · outbound
This paper cites Exploiting visual artifacts to expose deepfakes and face manipulations.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Exploiting visual artifacts to expose deepfakes and face manipulations
Reference 34
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ef0db15d-c892-49c4-9f39-138ae7df8e3c · outbound
This paper cites Emo- tions don’t lie: An audio-visual deepfake detection method using affective cues.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Emo- tions don’t lie: An audio-visual deepfake detection method using affective cues
Reference 35
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9bc000c9-199a-4dc6-81f0-9058d7085044 · outbound
This paper cites Does audio deepfake detection generalize? arXiv preprint arXiv:2203.16263, 2022.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Does audio deepfake detection generalize? arXiv preprint arXiv:2203.16263, 2022
Reference 36
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1761e696-aaa8-4fd5-9b5c-63c1bf77c4c1 · outbound
This paper cites Nguyen, Junichi Yamagishi, and Isao Echizen.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Nguyen, Junichi Yamagishi, and Isao Echizen
Reference 37
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f62a7ef7-de00-4d25-b642-f086ef6c0a94 · outbound
This paper cites Towards universal fake image detectors that generalize across generative models.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Towards universal fake image detectors that generalize across generative models
Reference 38
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b33bf91a-4459-486a-a57f-7206d11da1d0 · outbound
This paper cites Avff: Audio-visual feature fusion for video deepfake detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Avff: Audio-visual feature fusion for video deepfake detection
Reference 39
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2e33d572-82a6-49c0-a661-9a5ed21294cf · outbound
This paper cites Gpt-4: A large multimodal model.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Gpt-4: A large multimodal model
Reference 40
- Resolution
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- raw_fallback, observed 2026-08-07T15:27:03.709277Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a961ec6c-c6cd-4f8e-8810-3f959b1956e7 · outbound
This paper cites Deepfake generation and detection: A benchmark and survey.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Deepfake generation and detection: A benchmark and survey
Reference 41
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4939c70d-d9cf-4849-abff-6806947f0f82 · outbound
This paper cites Namboodiri, and C.V.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Namboodiri, and C.V
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.690146Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ce7db574-1fc5-4d78-8ee6-13722ead2071 · outbound
This paper cites Audio-visual deep neural network for robust person verification.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Audio-visual deep neural network for robust person verification
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.667273Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 998addff-3393-417d-b781-5e3d60ff255a · outbound
This paper cites Learning transferable visual models from natural language supervision.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Learning transferable visual models from natural language supervision
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.644870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ed3b185b-2c25-44f5-8a5d-80711d7b9155 · outbound
This paper cites Robust speech recognition via large-scale weak supervision.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Robust speech recognition via large-scale weak supervision
Reference 45
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 27b2ac9b-a357-416b-8236-577cc5b91d59 · outbound
This paper cites Faceforensics++: Learning to detect manipulated facial images.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Faceforensics++: Learning to detect manipulated facial images
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.606717Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4221d3cd-8174-470c-804c-b320f7db35c7 · outbound
This paper cites A comprehensive overview of deepfake: Generation, detection, datasets, and opportunities.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation A comprehensive overview of deepfake: Generation, detection, datasets, and opportunities
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.586152Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5bdf06cd-1658-4f2d-a4ef-2585d7efe552 · outbound
This paper cites Detecting deepfakes with self-blended images.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Detecting deepfakes with self-blended images
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:26:58.518035Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a3c8a52-071e-4a1b-9382-492116dc065e · outbound
This paper cites Representative forgery mining for fake face detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Representative forgery mining for fake face detection
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.548967Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 97f193b6-0890-403e-8b58-e6db7fecf709 · outbound
This paper cites Exploring Depth Information for Detecting Manipulated Face Videos.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Exploring Depth Information for Detecting Manipulated Face Videos
Reference 50
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T15:27:01.335494Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ae051bda-29c8-4dc1-a08a-1e6535fcd5a8 · outbound
This paper cites Tan, and Haizhou Li.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Tan, and Haizhou Li
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.522275Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0ad396e1-9008-44d0-909e-bce6a7cfc442 · outbound
This paper cites Deep spatial gradient and temporal depth learning for face anti-spoofing.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Deep spatial gradient and temporal depth learning for face anti-spoofing
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.497856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8654a873-3fb6-43db-b586-f4a3d6f549a9 · outbound
This paper cites Altfreezing for more general video face forgery detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Altfreezing for more general video face forgery detection
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.470186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation febc692d-c351-4c3a-85a6-300c68ce4ca3 · outbound
This paper cites Deepfake Video Detection Using Convolutional Vision Transformer.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Deepfake Video Detection Using Convolutional Vision Transformer
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:26:58.916792Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ddcbe21a-8038-433e-9d37-8d3b1f313f5f · outbound
This paper cites Binaural audio-visual localization.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Binaural audio-visual localization
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.445286Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b4697dcc-b1a5-47a8-ad45-b2d8fffe439d · outbound
This paper cites Identity- driven multimedia forgery detection via reference assistance.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Identity- driven multimedia forgery detection via reference assistance
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.421904Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 15ce0a97-bc90-4e7e-ac37-97abf628d8bb · outbound
This paper cites Tall: Thumbnail layout for deepfake video detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Tall: Thumbnail layout for deepfake video detection
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.390976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c6811e39-49e0-4c8c-af3b-f003898121cd · outbound
This paper cites Transcending forgery specificity with latent space augmentation for generalizable deepfake detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Transcending forgery specificity with latent space augmentation for generalizable deepfake detection
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.362476Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 971ad1d4-6480-44f9-a694-e2f7f915d7e2 · outbound
This paper cites DF40: Toward Next-Generation Deepfake Detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation DF40: Toward Next-Generation Deepfake Detection
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:26:59.305225Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d877f55-ac55-496c-9d20-c55c0911f808 · outbound
This paper cites GPT-ImgEval: A Comprehensive Benchmark for Diagnosing GPT4o in Image Generation.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation GPT-ImgEval: A Comprehensive Benchmark for Diagnosing GPT4o in Image Generation
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:26:59.364495Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d25b769b-48ca-4156-bb5f-d47bcb261003 · outbound
This paper cites Ucf: Uncovering common features for generalizable deepfake detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Ucf: Uncovering common features for generalizable deepfake detection
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.337860Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9c056045-81dc-401a-a5b1-e90a2e2f039f · outbound
This paper cites Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuning.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuning
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:26:59.498474Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ad1cfbbd-6071-4c67-919d-5c751b1c3a31 · outbound
This paper cites Avoid-df: Audio-visual joint learning for detecting deepfake.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Avoid-df: Audio-visual joint learning for detecting deepfake
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:03.032256Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation be58bad2-38dc-4944-941b-4c71e3c5c80e · outbound
This paper cites Exposing deep fakes using inconsistent head poses.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Exposing deep fakes using inconsistent head poses
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:02.912242Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4939e96a-4e65-4f9e-b493-fec38e132990 · outbound
This paper cites Audio Deepfake Detection: A Survey.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Audio Deepfake Detection: A Survey
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:26:59.790961Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f57e4aa7-b32c-4034-9cac-eafa94f7c76a · outbound
This paper cites Learning natural consistency representation for face forgery video detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Learning natural consistency representation for face forgery video detection
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:02.835435Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0a1ded16-7871-485e-a9f1-31875ef21b89 · outbound
This paper cites Inclusion 2024 Global Multimedia Deepfake Detection Challenge: Towards Multi-dimensional Face Forgery Detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Inclusion 2024 Global Multimedia Deepfake Detection Challenge: Towards Multi-dimensional Face Forgery Detection
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:27:00.152871Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7b594adb-5bb3-4472-b87f-5e8c0bae3f49 · outbound
This paper cites Multi-attentional deepfake detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Multi-attentional deepfake detection
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:02.717608Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e5f35ecf-5e29-4f4a-aa9d-05a896ab8679 · outbound
This paper cites Attention-based spatial-temporal multi-scale network for face anti-spoofing.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Attention-based spatial-temporal multi-scale network for face anti-spoofing
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:02.577494Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 98e6c56d-f524-4cca-8c56-5edb2bfa5436 · outbound
This paper cites Exploring temporal coherence for more general video face forgery detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Exploring temporal coherence for more general video face forgery detection
Reference 70
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:02.445239Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ddf7a907-6417-4d79-bc02-88e3e060afbe · outbound
This paper cites Learning deep features for discriminative localization.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Learning deep features for discriminative localization
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:02.349469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 80b7e914-261f-4337-9107-8595853eb3e8 · outbound
This paper cites Makelttalk: speaker-aware talking-head animation.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Makelttalk: speaker-aware talking-head animation
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:02.294628Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 80b73bbd-895d-4d40-88b8-38d16dff6ea2 · outbound
This paper cites Joint audio-visual deepfake detection.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Joint audio-visual deepfake detection
Reference 73
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:02.134020Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ec5cef83-b4fd-464f-a38d-b37ac7d8645e · outbound
This paper cites Lan- guagebind: Extending video-language pretraining to n-modality by language-based semantic alignment.
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation Lan- guagebind: Extending video-language pretraining to n-modality by language-based semantic alignment
Reference 74
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:27:02.020529Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
Observation 4929d710-214b-4f3a-b5a0-17abcb6b57a5 · inbound
CAM-VFD: Cross-Attention Multimodal Video Forgery Detection cites this paper.
CAM-VFD: Cross-Attention Multimodal Video Forgery Detection CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T15:13:25.042025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.