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Paper Citation Record · LEDGER

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors

As of 10 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2607.07216.

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

pith.paper-citation-record.v1
2607.07216 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-09T17:12:53.262559Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

  • verified exact11
  • verified fuzzy34
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f06f9376-bfba-4406-9be1-b7f7984bda54 · outbound

This paper cites Mesonet: a compact facial video forgery detection network.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Mesonet: a compact facial video forgery detection network

Reference 1

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raw_fallback, observed 2026-07-09T17:16:23.457171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:f0949e6c54470af8df74e165564fef309f79b4c9268b64c9a5fa6d95fac4abd2

Observation 80a19eac-db84-4bf5-abd9-fc38d963f640 · outbound

This paper cites Mechanistic Interpretability for AI Safety -- A Review.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Mechanistic Interpretability for AI Safety -- A Review

Reference 2

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verified exact
local_arxiv, observed 2026-07-09T17:16:23.155245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:fcaf5fa966c9813ae285f4a7f68ded024647d2bb0a1ad346c914126d5024e885

Observation 5ff2af12-e06e-46e6-9a89-875b24caae05 · outbound

This paper cites Hyperreenact: one- shot reenactment via jointly learning to refine and retarget faces.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Hyperreenact: one- shot reenactment via jointly learning to refine and retarget faces

Reference 3

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raw_fallback, observed 2026-07-09T17:16:23.500839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:03a5b3643a0c68d7eb07ce92bec24d0851e27b1c73f8bfeace5511a664803b76

Observation 94082c9d-6bc9-4c7b-8714-0086f7444de1 · outbound

This paper cites Protoexplorer: Interpretable foren- sic analysis of deepfake videos using prototype exploration and refinement.Information Visualization, 23(3):239–257,.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Protoexplorer: Interpretable foren- sic analysis of deepfake videos using prototype exploration and refinement.Information Visualization, 23(3):239–257,

Reference 4

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raw_fallback, observed 2026-07-09T17:16:23.502565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:89d6eeb4c9cb16f546f310b140edcf1dcb2e81483aece685c680ab6cf7f90b6b

Observation 5b4bb117-b2ce-472e-8d1e-6de3ea67815c · outbound

This paper cites Self-supervised learning of adversarial example: Towards good generalizations for deepfake detection.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Self-supervised learning of adversarial example: Towards good generalizations for deepfake detection

Reference 5

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raw_fallback, observed 2026-07-09T17:16:23.478652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:fb323d0d2ed22ab684a082deadb7c24f5accf2a911d997893cfed9f9f0cb744e

Observation 7f34a5ae-90a5-49a9-9b4b-8ab113de554b · outbound

This paper cites Simswap: An efficient framework for high fidelity face swapping.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Simswap: An efficient framework for high fidelity face swapping

Reference 6

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raw_fallback, observed 2026-07-09T17:16:23.469236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:81ba40ebe6f31252411283a2323c15b97824b99cb7de6097c2ff0fd9ad6439c7

Observation e4767285-c2b7-4910-832e-7025a0391845 · outbound

This paper cites Deep fakes: A looming challenge for privacy, democracy, and national security.Calif.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Deep fakes: A looming challenge for privacy, democracy, and national security.Calif

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:a462d903cdf255ca3dc7bdabd2663da7f756033c2a24e3239330c9aa2e4d3e4b

Observation eb13ca7e-63b4-4a29-adc1-cea9cb3afdd9 · outbound

This paper cites Xception: Deep learning with depthwise separable convolutions.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Xception: Deep learning with depthwise separable convolutions

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:ff3100d43e751b13a4f367990e73bf64e4eb851956f61b91cdfa1ba039b0c1fb

Observation 1e6efa9b-3af4-4148-b73e-aa9e997f861e · outbound

This paper cites Face transformer: Towards high fidelity and accurate face swapping.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Face transformer: Towards high fidelity and accurate face swapping

Reference 9

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raw_fallback, observed 2026-07-09T17:16:23.492934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:afe44f456617b0925d02002aa564e62e43fd1e04d021f85b718150b8161dcfb0

Observation cfd9182b-44c7-4c7e-9bd8-1ad9be94c2da · outbound

This paper cites The DeepFake Detection Challenge (DFDC) Dataset.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors The DeepFake Detection Challenge (DFDC) Dataset

Reference 10

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local_arxiv, observed 2026-07-09T17:16:23.161540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:58371f43baee6725f025afc56bab3e07099282936ebbdc9bca19bb7a1bce227b

Observation 726c8d11-9155-4b7a-a20c-e3162b0ce112 · outbound

This paper cites Learning Encoding-Decoding Direction Pairs to Unveil Concepts of Influence in Deep Vision Networks.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Learning Encoding-Decoding Direction Pairs to Unveil Concepts of Influence in Deep Vision Networks

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-07-22T01:22:14.093143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:0b9cd4d652e70b9c4bc3891053fa1f23718cea27637669476d21a91afa838693

Observation 3384f98a-f210-448e-9238-b419f7e3db51 · outbound

This paper cites Audcast: Audio-driven human video generation by cascaded diffusion transformers.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Audcast: Audio-driven human video generation by cascaded diffusion transformers

Reference 12

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raw_fallback, observed 2026-07-09T17:16:23.507789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:f07d29d306f88bf69feed32cff30d295870e30306fd424a4f02ed5fc97b8a019

Observation a2e4bb81-3bbe-48e6-a194-4300a02c5fec · outbound

This paper cites Forgerynet: A versatile benchmark for comprehensive forgery analysis.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Forgerynet: A versatile benchmark for comprehensive forgery analysis

Reference 13

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raw_fallback, observed 2026-07-09T17:16:23.472807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:caf918c1b28123ae5451899ff87e1cdca6cd33e394d3986eb1bbc3b5b01d01c6

Observation fc21d4d7-66d6-4594-bc4d-5516fe59b36e · outbound

This paper cites Exddv: A new dataset for explainable deepfake detection in video.arXiv preprint arXiv:2503.14421, 2025.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Exddv: A new dataset for explainable deepfake detection in video.arXiv preprint arXiv:2503.14421, 2025

Reference 14

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arxiv_id, observed 2026-07-09T17:16:23.157924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:486dbe8c002d547082be903c9c5cdcae2b50c39384fdf7b3e3674d13491ff015

Observation fa949ac6-b2a3-4e63-9760-7d3e6eea793f · outbound

This paper cites Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Traces.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Traces

Reference 15

Resolution
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local_arxiv, observed 2026-07-09T17:16:23.135473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:c47199435177a76666cd86e9a6458612d1e88698c2458b1534267184d0910ebd

Observation b77e1282-996f-4141-8465-ebdc250416be · outbound

This paper cites Deeperforensics-1.0: A large-scale dataset for real-world face forgery detection.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Deeperforensics-1.0: A large-scale dataset for real-world face forgery detection

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:70dc2a9825e58ca3706ae2433f91a3b9a187940cc761676c9a1005feef5cdae2

Observation ad9fbbd0-f456-4e4d-a6c1-775f18412472 · outbound

This paper cites A comprehen- sive survey of deepfake generation and detection techniques in audio-visual media.ICCK Journal of Image Analysis and Processing, 1(2):73–95, 2025.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors A comprehen- sive survey of deepfake generation and detection techniques in audio-visual media.ICCK Journal of Image Analysis and Processing, 1(2):73–95, 2025

Reference 17

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raw_fallback, observed 2026-07-09T17:16:23.511790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:1461fc6328b14397befa0fa73f920396af117a8cbe3debc0852a78fa6fe7c04a

Observation 2790c457-0edd-426d-b4aa-93f7dc0cf49a · outbound

This paper cites Smooth- swap: A simple enhancement for face-swapping with smooth- ness.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Smooth- swap: A simple enhancement for face-swapping with smooth- ness

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:b859dc38cfba98e966a68654ac9d9485f80b4b3628b28de87fd0188b7c12e435

Observation 00524056-5b79-4e63-850d-fcd7441e8d9b · outbound

This paper cites Diffface: Diffusion-based face swapping with facial guidance.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Diffface: Diffusion-based face swapping with facial guidance

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:a67d252ddf98d483f326144168ac28135d98d09419d8059ce9cc02b2af20b232

Observation 1329c9b7-547b-4b47-b3a1-b454951415b2 · outbound

This paper cites Beyond spa- tial frequency: Pixel-wise temporal frequency-based deepfake video detection.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Beyond spa- tial frequency: Pixel-wise temporal frequency-based deepfake video detection

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:e9df58b20c8530cc1e0b21a129937c0a6838bfa939dd8fc804385b12921447a4

Observation e3669fa8-b382-405c-8522-44f4c283e4dd · outbound

This paper cites Fast face-swap using convolutional neural networks.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Fast face-swap using convolutional neural networks

Reference 21

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:0d6c2a3284f38cb895126cf5aebfb45eeef68b9fc39fe70ac31875543143fe2d

Observation 4de2f26e-5dfd-4af6-a5bc-c817f74d2ea5 · outbound

This paper cites In ictu oculi: Exposing ai created fake videos by detecting eye blinking.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors In ictu oculi: Exposing ai created fake videos by detecting eye blinking

Reference 22

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:bf88ed7328413e6ecd49d24758102cca9ca3c83f561ac1cc55b79e4b8c26a268

Observation ddb84e01-a893-4d19-8fe6-899e64931a9f · outbound

This paper cites Celeb-df: A large-scale challenging dataset for deepfake forensics.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Celeb-df: A large-scale challenging dataset for deepfake forensics

Reference 23

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raw_fallback, observed 2026-07-09T17:16:23.455278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:c5dd1a0b6e0e09a4dc5abbe822e4c5364be12411cbcfe2bd8cdfd46dd1d23444

Observation 8bebe635-bf4a-498f-a7d0-c1e0184f5c50 · outbound

This paper cites Deepfacelab: Integrated, flexible and extensible face-swapping framework.Pattern Recognition, 141:109628, 2023.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Deepfacelab: Integrated, flexible and extensible face-swapping framework.Pattern Recognition, 141:109628, 2023

Reference 24

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raw_fallback, observed 2026-07-09T17:16:23.515698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:a9a394db53cddc46bd2b9e715ca5b137aa666f34129062dead23f6c39700e15c

Observation 8a0cdf33-a457-4bd5-92ff-56d38e6950c9 · outbound

This paper cites Canonswap: High- fidelity and consistent video face swapping via canonical space modulation.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Canonswap: High- fidelity and consistent video face swapping via canonical space modulation

Reference 25

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raw_fallback, observed 2026-07-09T17:16:23.459039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:8095b55c2079be9d283cc4b05418f22cf3ae2e981df385dbeea33c53ec955c1d

Observation 74a7e4fa-b560-4381-b844-5df561239c5a · outbound

This paper cites Explainable ai for deepfake detection.Applied Sciences, 15(2):725.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Explainable ai for deepfake detection.Applied Sciences, 15(2):725

Reference 26

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raw_fallback, observed 2026-07-09T17:16:23.462074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:a718b164e0ead45d5650f95c24c6d13c0656f6071fcdffef23a178a0c4b188f4

Observation 86656b58-89f0-40ef-98b5-66d4d4a605dc · outbound

This paper cites Multi-spectral Class Center Network for Face Manipulation Detection and Localization.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Multi-spectral Class Center Network for Face Manipulation Detection and Localization

Reference 27

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local_arxiv, observed 2026-07-09T17:16:23.120652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:6353467a8cbb31955b8176e39b18f9f00380199b6dc53444ca8efd63d678fac9

Observation 4ca256f5-a58f-4e80-bd50-d60eb5d4151a · outbound

This paper cites Ddl: A dataset for interpretable deepfake detec- tion and localization in real-world scenarios.arXiv preprint arXiv:2506.23292, 2025.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Ddl: A dataset for interpretable deepfake detec- tion and localization in real-world scenarios.arXiv preprint arXiv:2506.23292, 2025

Reference 28

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arxiv_id, observed 2026-07-09T17:16:23.143588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:53ba68b2bdf814fc9502cb5c52ea6002fb0b27f41d1580ddb170479180738c1b

Observation bc0bf201-baf9-44fa-85aa-09fd5acd5122 · outbound

This paper cites Robust Semantic Interpretability: Revisiting Concept Activation Vectors.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Robust Semantic Interpretability: Revisiting Concept Activation Vectors

Reference 29

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verified exact
local_arxiv, observed 2026-07-09T17:16:23.151074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:93cf54bfd4f0da00b6e442a5787c3f513ba226fc25596d5524fe9d311c2e84c4

Observation 126d30da-d6ef-43b8-9100-8c095ad3ead2 · outbound

This paper cites A lip sync expert is all you need for speech to lip generation in the wild.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors A lip sync expert is all you need for speech to lip generation in the wild

Reference 30

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raw_fallback, observed 2026-07-09T17:16:23.463923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:7d541745653e02d993518e800ff0137a198a0b721fd960c529e30d6d507fbde2

Observation dc093ec6-07cc-44ab-9ff8-a8750dddce96 · outbound

This paper cites Thinking in frequency: Face forgery detection by mining frequency-aware clues.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Thinking in frequency: Face forgery detection by mining frequency-aware clues

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.470960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:fc8e5a38d1af4ce5f5169ce0e3e80d278954dd43080f641a70de4034ff594a1c

Observation a2e02e97-79a1-46b5-8431-77a333a808f5 · outbound

This paper cites SkyReels-A1: Expressive Portrait Animation in Video Diffusion Transformers.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors SkyReels-A1: Expressive Portrait Animation in Video Diffusion Transformers

Reference 32

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local_arxiv, observed 2026-07-09T17:16:23.131843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:cb521e7247f468898ce9ee5da84f027b6b3e50966d7f93ac24df92f719bc2f2a

Observation 78ab78a1-3ffa-4cf8-9e53-e583aa543789 · outbound

This paper cites Fsrt: Fa- cial scene representation transformer for face reenactment from factorized appearance head-pose and facial expression features.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Fsrt: Fa- cial scene representation transformer for face reenactment from factorized appearance head-pose and facial expression features

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.474478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:6654652a4149221d80da122fbb6b79c42bb3bb1a52f1ad6f8c86527dbd89ceee

Observation b8d6cd68-486a-4169-bfe3-f0bc761f5d24 · outbound

This paper cites FaceForen- sics++: Learning to detect manipulated facial images.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors FaceForen- sics++: Learning to detect manipulated facial images

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.513613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:11a61a29cebebf332adcac3060b9abdff90e1855f35325d1d9657862654ba889

Observation c20279c6-f48c-405e-9a16-701ce5dec0a0 · outbound

This paper cites Grad- cam: Visual explanations from deep networks via gradient- based localization.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Grad- cam: Visual explanations from deep networks via gradient- based localization

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.450222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:6a493cbeace8acfefc8585e5c70ccf2e71170c479fde05af20c298e65ef2d335

Observation e7f4ab5c-da87-4d72-af4f-4f6b121a46db · outbound

This paper cites Extracting local information from global representations for interpretable deepfake detection.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Extracting local information from global representations for interpretable deepfake detection

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.446517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:6ccbb3c9ecae886590f7ffa3e462a4fd332439b3aa23e199731281d14cf1b3f2

Observation 0d178325-73dd-4f59-84a5-0730e98479df · outbound

This paper cites Face2face: Real-time face capture and reenactment of rgb videos.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Face2face: Real-time face capture and reenactment of rgb videos

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.451859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:7b87659696bb2288f8722057151d176a3a48f78eca1bc137269834846b3532f5

Observation 7bed60b5-617e-499c-a562-de725fff7840 · outbound

This paper cites Dynamicface: High-quality and consistent face swapping for image and video using composable 3d facial priors.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Dynamicface: High-quality and consistent face swapping for image and video using composable 3d facial priors

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.448199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:ab6166cd598abd335079736c35b8ff0d95243b6366758089c4f23d58b100b843

Observation 6ade0037-c54f-440e-8e68-63f2225df1ed · outbound

This paper cites Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detection.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detection

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-07-09T17:16:23.140023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:cba3f18aa3d3a5916e30f6ef96bcfedca73db26b7fe9c6b72aef64836cdb3d9d

Observation a307bc51-2e95-429f-b0cb-5fd059737066 · outbound

This paper cites Df40: Toward next-generation deepfake detection.Advances in Neural Information Process- ing Systems, 37:29387–29434, 2024.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Df40: Toward next-generation deepfake detection.Advances in Neural Information Process- ing Systems, 37:29387–29434, 2024

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.444043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:27dab7d44995036a00f1a5531e4af9d3951f4e50e860f1c1b631cdaab4852c7c

Observation b5c20973-e1be-4bd3-b196-1b5a45930dfa · outbound

This paper cites Exposing deep fakes using inconsistent head poses.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Exposing deep fakes using inconsistent head poses

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.466481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:bf747614bc65179eb4cdc8eb406552d90129b60a8e6f16c4d269205e492c01ab

Observation 68c15884-e1b7-4814-b553-2b6cb8b2b89f · outbound

This paper cites Dreamid: High-fidelity and fast diffusion-based face swapping via triplet id group learning.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Dreamid: High-fidelity and fast diffusion-based face swapping via triplet id group learning

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.494686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:3e9bf2263b7a5fe7e50148d16c9573d1086792771335d17824f060aa53e6573e

Observation a0c0dcc8-3dd5-4c68-b3ec-27391620f323 · outbound

This paper cites Unlocking the Hidden Potential of CLIP in Generalizable Deepfake Detection.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Unlocking the Hidden Potential of CLIP in Generalizable Deepfake Detection

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-07-09T17:16:23.147276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:85b8b7bf691347dc3e21f1a9d0bc4117c1400be8b9a0d9a7c143ba8180cf66ac

Observation 2082b13f-8570-4109-bdd0-d4d88aba0610 · outbound

This paper cites Sadtalker: Learning realistic 3d motion coefficients for stylized audio- driven single image talking face animation.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Sadtalker: Learning realistic 3d motion coefficients for stylized audio- driven single image talking face animation

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.505854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:a9646b5f293cb40b617ce1996eff06fe93a7a77b0ae6a2fb24a99fb210b85e19

Observation da78b9d4-0e9e-4acc-b1dc-7bdd4349478c · outbound

This paper cites Diffswap: High-fidelity and controllable face swapping via 3d-aware masked diffusion.

Why Fake ? Unveiling the Semantic Vocabulary of Deepfake Detectors Diffswap: High-fidelity and controllable face swapping via 3d-aware masked diffusion

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T17:16:23.509594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-09T17:12:53.262559Z digest=sha256:de94fbbc907a295b5aa42711debeb8298b87a7088c4bfeab251e81fb33ded856

Pith citing papers

No inbound Pith citation observations are available.