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Paper Citation Record · LEDGER

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization

As of 11 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2509.07993.

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

pith.paper-citation-record.v1
2509.07993 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:12:32.909169Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

70 of 70 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e6184316-4339-41c9-8a93-f82ea25eca36 · outbound

This paper cites Parents and Children: Distinguishing Multimodal DeepFakes from Natural Images.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Parents and Children: Distinguishing Multimodal DeepFakes from Natural Images

Reference 2

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Observation f71e46f9-808e-4edd-898d-df836e8ef0a6 · outbound

This paper cites Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System

Reference 3

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Observation 87b1fd33-5db2-489c-9a5c-cf6bdf729bb6 · outbound

This paper cites Cifake: Image classifica- tion and explainable identification of ai-generated synthetic images.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Cifake: Image classifica- tion and explainable identification of ai-generated synthetic images

Reference 4

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Observation 80513353-b0b7-4356-87ea-61fe55b29098 · outbound

This paper cites Dark experience for general continual learning: a strong, simple baseline.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Dark experience for general continual learning: a strong, simple baseline

Reference 5

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Observation 67f49e8d-f9c1-4049-bd00-ae9d0a8a2aa9 · outbound

This paper cites Harnessing the power of text-image contrastive models for automatic detection of on- line misinformation.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Harnessing the power of text-image contrastive models for automatic detection of on- line misinformation

Reference 6

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Observation 8fd24f3f-8db1-41c0-a826-813ea4ba2aab · outbound

This paper cites Masked Conditional Diffusion Model for Enhancing Deepfake Detection.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Masked Conditional Diffusion Model for Enhancing Deepfake Detection

Reference 7

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Observation 7bd0f2d1-8e8d-4d89-b428-0f4d25d1a44c · outbound

This paper cites Fakecatcher: Detection of synthetic portrait videos using biological sig- nals.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Fakecatcher: Detection of synthetic portrait videos using biological sig- nals

Reference 8

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Observation 39015386-96f0-48cd-827f-e2f7fbd9f3d9 · outbound

This paper cites Forensictrans- fer: Weakly-supervised domain adaptation for forgery detec- tion.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Forensictrans- fer: Weakly-supervised domain adaptation for forgery detec- tion

Reference 9

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Observation 4585362d-7c27-4eb0-b087-ad2dbe980d62 · outbound

This paper cites On the detection of digital face manipulation.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization On the detection of digital face manipulation

Reference 10

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Observation 1e9feb2c-205d-4adc-a9dd-ebdef4c11773 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 11

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Observation db69f514-3b28-44ff-a547-9fe6d91a77f9 · outbound

This paper cites Attacking identity semantics in deepfakes via deep feature fusion.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Attacking identity semantics in deepfakes via deep feature fusion

Reference 12

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Observation eeead055-d11c-4e70-a153-cec6cfe84f0d · outbound

This paper cites Synthesizing black-box anti-forensics deepfakes with high visual quality.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Synthesizing black-box anti-forensics deepfakes with high visual quality

Reference 13

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This paper cites Detection, Attribution and Localization of GAN Generated Images.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Detection, Attribution and Localization of GAN Generated Images

Reference 14

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Observation 56c3fa0d-91d9-4bc5-824d-670a3057b6fa · outbound

This paper cites An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks

Reference 15

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Observation 91809140-fb64-40a5-897a-f22e1521d602 · outbound

This paper cites Studies of mind and brain: Neural principles of learning, perception, development, cognition, and motor control.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Studies of mind and brain: Neural principles of learning, perception, development, cognition, and motor control

Reference 16

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Observation 927bbfc9-ff3d-4ea9-9488-8e630ffc7fbb · outbound

This paper cites Deepfake detection by analyzing convolutional traces.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Deepfake detection by analyzing convolutional traces

Reference 17

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Observation d1a557ab-3a3c-4bac-8bb1-5e4e29f3f29d · outbound

This paper cites Robust attentive deep neural network for detecting gan- generated faces.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Robust attentive deep neural network for detecting gan- generated faces

Reference 18

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This paper cites Deep fake image detection based on pairwise learning.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Deep fake image detection based on pairwise learning

Reference 19

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Observation ec8a31ec-f622-431e-9fa3-2e0ca0de8fdb · outbound

This paper cites Improving the generalization ability of deepfake detection via disentangled representation learning.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Improving the generalization ability of deepfake detection via disentangled representation learning

Reference 20

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Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization De- tecting cnn-generated facial images in real-world scenarios

Reference 21

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Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Unresolved cited work

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Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Unresolved cited work

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This paper cites Overcoming catastrophic forgetting in neu- ral networks.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Overcoming catastrophic forgetting in neu- ral networks

Reference 24

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This paper cites DeepFakes: a New Threat to Face Recognition? Assessment and Detection.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization DeepFakes: a New Threat to Face Recognition? Assessment and Detection

Reference 25

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This paper cites Towards generalized deepfake detection with continual learning on limited new data.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Towards generalized deepfake detection with continual learning on limited new data

Reference 26

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This paper cites Faster than lies: Real-time deepfake detection using binary neural networks.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Faster than lies: Real-time deepfake detection using binary neural networks

Reference 27

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This paper cites How Generalizable are Deepfake Image Detectors? An Empirical Study.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization How Generalizable are Deepfake Image Detectors? An Empirical Study

Reference 28

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This paper cites A continual deepfake detection benchmark: Dataset, meth- ods, and essentials.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization A continual deepfake detection benchmark: Dataset, meth- ods, and essentials

Reference 29

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Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization In ictu oculi: Exposing ai created fake videos by detecting eye blinking

Reference 30

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Observation d5ffdd39-82d0-4efa-9dbf-0d5d2c28392f · outbound

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

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Celeb-df: A large-scale challenging dataset for deep- fake forensics

Reference 31

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Observation f965fe47-db1c-409d-aa2a-457b6f90749b · outbound

This paper cites Exploring disentangled content information for face forgery detection.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Exploring disentangled content information for face forgery detection

Reference 32

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This paper cites Detecting Multimedia Generated by Large AI Models: A Survey.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Detecting Multimedia Generated by Large AI Models: A Survey

Reference 33

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This paper cites Preserving fairness generalization in deepfake detec- tion.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Preserving fairness generalization in deepfake detec- tion

Reference 34

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This paper cites Global tex- ture enhancement for fake face detection in the wild.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Global tex- ture enhancement for fake face detection in the wild

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:28.816575Z digest=sha256:5a92e6e2eac5068f789b3ed3d5d5d22857a7a93c2b53372e798bf1a6205daa2c

Observation d61917a2-fab9-4ce0-9e68-4bf5365e2d01 · outbound

This paper cites Gradient episodic memory for continual learning.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Gradient episodic memory for continual learning

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:39.244407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:28.877058Z digest=sha256:b9ffebf1d6461371288b94346e5ae6a35634de4bfe724bf6cc2789bf026d5e39

Observation 0f62b40c-fbfe-4e5f-b239-87b668d1f2e9 · outbound

This paper cites Detecting images generated by deep diffusion models using their lo- cal intrinsic dimensionality.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Detecting images generated by deep diffusion models using their lo- cal intrinsic dimensionality

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:39.014779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:28.931810Z digest=sha256:359ca359cfdfd3ffa18d35c2cca46efac33aede5fdf7597248d5746b580a4709

Observation 85968d59-d128-4791-a74d-987a6eb5a38d · outbound

This paper cites Incremental learning for the detection and clas- sification of gan-generated images.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Incremental learning for the detection and clas- sification of gan-generated images

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:38.778894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:29.034904Z digest=sha256:08ffc77c30030260a815285241d3b231ff55e46d105bb8b2a565f2efe98715ab

Observation 301bd7c3-c57e-4ebc-ba5d-1593232bbf9e · outbound

This paper cites Deepfakes genera- tion and detection: State-of-the-art, open challenges, coun- termeasures, and way forward.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Deepfakes genera- tion and detection: State-of-the-art, open challenges, coun- termeasures, and way forward

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:38.604646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:29.096734Z digest=sha256:3ffee1e619878b8008f8d6309333a8b57d92c1e6cdc0fa26e531e1d6bbe352f1

Observation 66a9ed58-e97a-472e-8dac-1ed239a75cb4 · outbound

This paper cites GBDF: Gender Balanced DeepFake Dataset Towards Fair DeepFake Detection.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization GBDF: Gender Balanced DeepFake Dataset Towards Fair DeepFake Detection

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-05T14:12:29.226417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:12:29.226417Z digest=sha256:6c4213692aca7a731fac8f440ff9fc79e47cad2988a05cf437e46f6a8d617b48

Observation 132e6df7-9975-49a9-b14b-d709a4cc33e0 · outbound

This paper cites Multi-task learning for detecting and segment- ing manipulated facial images and videos.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Multi-task learning for detecting and segment- ing manipulated facial images and videos

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:38.305770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:29.324504Z digest=sha256:63c4aa61f0a47254806af7d1175486b804d6c76ce45fc6507c99e4488ade4a67

Observation fde01c05-c11d-446d-840a-033443824deb · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-05T14:12:29.417039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:12:29.417039Z digest=sha256:b3d8df1338add405eafb2e72b97ca10bfe318c3ff67976d58e3e4ce78e2d3e0e

Observation 1c9e0e42-e22f-4156-bfce-bea5056c5c81 · outbound

This paper cites Dfil: Deepfake incremental learning by exploiting domain-invariant forgery clues.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Dfil: Deepfake incremental learning by exploiting domain-invariant forgery clues

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:37.937304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:29.509985Z digest=sha256:983907ec972e11583041bd40ca9ad16f8a5ced0ededb9e9dbe7892763a51416f

Observation 127cd40e-5128-4963-a58d-ede83acb2c55 · outbound

This paper cites Learning a deep dual-level network for robust deepfake detection.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Learning a deep dual-level network for robust deepfake detection

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:37.655348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:29.603827Z digest=sha256:7131d0ec905ff9bee9d5f39a5f74943bf9f942589c1ee8681350f69b8d655476

Observation 1d9f813e-c364-4e7e-a537-081ad00f257b · outbound

This paper cites Mobilenetv4: universal models for the mobile ecosystem.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Mobilenetv4: universal models for the mobile ecosystem

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:37.350343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:29.724525Z digest=sha256:dff5324f375647a210e64accd0205087349f3f4d97673737bb4855984e93d8c8

Observation 09e5c09a-f111-4bb7-9a8c-0dd28f626f73 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-05T14:12:29.826405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:12:29.826405Z digest=sha256:68365c9d311581d351efa510bb192921f3999e4ea8654e32c20cf7d4f41ab4c4

Observation 40f2d71d-1d61-46c5-8a1f-6909817928e5 · outbound

This paper cites ImageNet-21K Pretraining for the Masses.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization ImageNet-21K Pretraining for the Masses

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-05T14:12:29.948773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:12:29.948773Z digest=sha256:99bb88ceacf04fb736583e55a2721e5f22bb2a6682355f4ba14a64d65838ed12

Observation ee41bcc1-259b-433a-b2cf-69e99303d36f · outbound

This paper cites Experience replay for continual learning.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Experience replay for continual learning

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:37.217150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:30.055959Z digest=sha256:a490217db9dcbca8de5715d2f3846672855855815320713904e28d16357cf1f3

Observation 6eeb57f4-15ed-4ef1-bebb-69d276f3e468 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization High-resolution image synthesis with latent diffusion models

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:37.071014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:30.166115Z digest=sha256:ac15da5a0855acc5b3eaf1980de109d4ca2b03bc73623e64d52384f4b48f4f22

Observation 114039ec-82cf-4a5f-8204-cb7d2f2833da · outbound

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

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Faceforen- sics++: Learning to detect manipulated facial images

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:36.896590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:30.227737Z digest=sha256:869871869ae3bdd7d3a979b5a7698189a2e42ee0f276154b877865afa97a6a1c

Observation 2788461b-afe7-4f9f-82ef-92c074de5421 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Photorealistic text-to-image diffusion models with deep language understanding

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:36.722304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:30.430587Z digest=sha256:f4fa1c5bfbf70d8ea9b5bd68dab493b05f2f7556f2615490f5dc0f2b1255060f

Observation 40806fdb-3cff-4534-8e8e-aa8f49a7cf28 · outbound

This paper cites Error sensitivity modulation based experience replay: Mitigating abrupt representation drift in continual learning.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Error sensitivity modulation based experience replay: Mitigating abrupt representation drift in continual learning

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:36.542597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:30.611992Z digest=sha256:78894d64fcb5b424d517152484567e7776cd934162a9ce219f0afc68eb856622

Observation 8a18fa8b-8382-474f-9777-dd54caaa9939 · outbound

This paper cites Con- tinuous fake media detection: Adapting deepfake detectors to new generative techniques.Comput.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Con- tinuous fake media detection: Adapting deepfake detectors to new generative techniques.Comput

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:36.399200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:30.789173Z digest=sha256:46d07ec8aff5f4604b35dee3e8bd3573f8c2a454b65000783452a4c134565692

Observation b2f01995-ce8f-4266-a2bc-171e9bf68be2 · outbound

This paper cites An examination of fairness of ai models for deepfake detection.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization An examination of fairness of ai models for deepfake detection

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:36.224251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:30.961889Z digest=sha256:12de57ad6981bda6a259e575371ba85a8970b8f6d35337a06d4fd3dce7780a27

Observation 4fdce8f3-4a48-4974-a0d5-f1b04e001aa7 · outbound

This paper cites En- hancing generalization ability in deepfake detection via con- tinual learning.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization En- hancing generalization ability in deepfake detection via con- tinual learning

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:36.045485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:30.997427Z digest=sha256:c476de30a34e31501486b16f9c7e9ae8e96c5d05c3e455ecbf005e83c7c0b2b7

Observation a337adb3-2a39-42bc-a370-f08f22dff0bf · outbound

This paper cites Three scenarios for continual learning.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Three scenarios for continual learning

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-05T14:12:31.009858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:12:31.009858Z digest=sha256:d7f87b601901ea8fa45df6a51fece996fd059990b9b02d7f02969c6dd6c718f6

Observation f56a4823-4d5e-4d28-ae6d-1ea7758719ba · outbound

This paper cites Fastvit: A fast hybrid vision transformer using structural reparameterization.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Fastvit: A fast hybrid vision transformer using structural reparameterization

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:35.898760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:31.119882Z digest=sha256:8e878739968178ca67e83fa5d98846229596badefaa1ab271c494a6aa979f5b1

Observation 898775ad-5d33-4de2-b7ce-3a725da5ec28 · outbound

This paper cites Cnn-generated images are sur- prisingly easy to spot.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Cnn-generated images are sur- prisingly easy to spot

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:35.763339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:31.253748Z digest=sha256:29b9b655092df72caf32f298cd21967eaa0d61cfd09b0ca625f2e48e594555cc

Observation 305ea4b2-6abb-4bc6-9bc5-47c78a85d9d4 · outbound

This paper cites Deepfake detectors and datasets exhibit racial and gender bias, usc study shows.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Deepfake detectors and datasets exhibit racial and gender bias, usc study shows

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:35.575903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:31.354516Z digest=sha256:bb71579424c993b02a3e084630776eeabe341a60cae5211d951a9104461c34ef

Observation babfd60e-8e06-42a9-ba9a-a2eebe1dfd05 · outbound

This paper cites Con- vnext v2: Co-designing and scaling convnets with masked autoencoders.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Con- vnext v2: Co-designing and scaling convnets with masked autoencoders

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:35.257418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:31.505456Z digest=sha256:3975ade80818e432cc6f9489192f12a59a875977091b64b9bf8286b8cf1d1b74

Observation 46ca9dcc-d945-46e4-9d1c-d074de562001 · outbound

This paper cites Analyzing Fairness in Deepfake Detection With Massively Annotated Databases.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Analyzing Fairness in Deepfake Detection With Massively Annotated Databases

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-05T14:12:31.623379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:12:31.623379Z digest=sha256:3620fa06477610e571aa7b3b70ed15f14f745ba9b399894c71b59fe05321c067

Observation 87bb33af-79b3-4fc7-8040-e914a09d8a50 · outbound

This paper cites Yan et al.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Yan et al

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:35.083867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:31.749058Z digest=sha256:074c5fb228b13d2445f4710a14e176694f485b0106faf0f3ce937334d820a4e1

Observation 8615148c-2404-44fc-ab30-611c30dc34b7 · outbound

This paper cites Ucf: Uncovering common features for generalizable deep- fake detection.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Ucf: Uncovering common features for generalizable deep- fake detection

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:34.962084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:31.873986Z digest=sha256:108e953ee58805f5c6638b9ce691f1accdc42ccdda2cf2c5c407f1e7d21231ff

Observation ea7c3680-82eb-4d01-b48e-372642163c85 · outbound

This paper cites Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuning.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuning

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-05T14:12:32.011950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:12:32.011950Z digest=sha256:c107202c618a7a068f850c536a8452d21b946766ffd9efa0d6f3c87d6c8c7bcf

Observation 9c862119-69f1-4eef-abdc-db1d2985d5d5 · outbound

This paper cites CrossDF: Improving Cross-Domain Deepfake Detection with Deep Information Decomposition.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization CrossDF: Improving Cross-Domain Deepfake Detection with Deep Information Decomposition

Reference 65

Resolution
verified exact
local_arxiv, observed 2026-08-05T14:12:33.337559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:32.092246Z digest=sha256:ab363d72b8003febd04e0fc4618ec66f767b3dfd94f3bfff07e6d5dad12a6dd7

Observation 10557148-736a-41b6-aa0a-ac9e6c774970 · outbound

This paper cites Exposing deep fakes using inconsistent head poses.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Exposing deep fakes using inconsistent head poses

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:34.765690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:32.225393Z digest=sha256:99ebe91acc12240263b3636853d97a7c87a3ccf3ca04c1a3a24f751b8cf331ea

Observation 51b69acc-9a1d-46d9-ba42-b848babf0d56 · outbound

This paper cites Towards understanding the generalization of deepfake detectors from a game-theoretical view.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Towards understanding the generalization of deepfake detectors from a game-theoretical view

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:34.594145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:32.322754Z digest=sha256:9d9e0a134dac63e783a0ec9165a4dc8664986bb1948431a3771a44cebf7f3b0b

Observation 68a815cf-a726-4810-a0b6-54b7845a1f83 · outbound

This paper cites Face anti-spoofing via disentangled represen- tation learning.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Face anti-spoofing via disentangled represen- tation learning

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:34.449101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:32.470660Z digest=sha256:ea5130e805fe5c7fac0ec3d0ca1f328b24cfe2e97217c935df1e59d5e5190894

Observation 9bb6214b-8c08-4965-916c-7d35b9f882a9 · outbound

This paper cites X-Transfer: A Transfer Learning-Based Framework for GAN-Generated Fake Image Detection.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization X-Transfer: A Transfer Learning-Based Framework for GAN-Generated Fake Image Detection

Reference 69

Resolution
verified exact
local_arxiv, observed 2026-08-05T14:12:33.140915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:32.649109Z digest=sha256:ca64c8c8a7bc60a97f4e0c1985cfb7dead53d6022f5be5717f17de2f63f7d722

Observation d8621a67-31d3-48d8-9a93-a8f2cde6482c · outbound

This paper cites Few-shot learning for misinformation detection based on contrastive models.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Few-shot learning for misinformation detection based on contrastive models

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:34.290802Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T14:12:32.800390Z digest=sha256:2cde5b6840bb71f720503a334fb6ede5812163fdcb53e3ff478cdddbf72d7871

Observation 3e63e9d9-5872-4137-aa3f-e08611ca5edc · outbound

This paper cites Wilddeepfake: A challenging real-world dataset for deepfake detection.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization Wilddeepfake: A challenging real-world dataset for deepfake detection

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:12:34.105465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T14:12:32.909169Z digest=sha256:9bf6118d763064d7eeb40388951307cdc4a832e748329864ec963d922542e641

Pith citing papers

No inbound Pith citation observations are available.