Paper Citation Record · LEDGER

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

As of 14 August 2026, this Paper Citation Record lists 100 of 128 outbound references and 11 inbound Pith citation observations for arXiv:2505.18660.

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

pith.paper-citation-record.v1
2505.18660 v5

Coverage vector

measured 100 of 128 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:31:32.169821Z

measured 111 of 111 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T15:38:27.960723Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-09T07:36:04.452062Z

Reference resolution

100 of 128 outbound references displayed

verified exact0
verified fuzzy46
unresolved54
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d238cb09-4d33-4df8-9d7c-c2824e8abe5f · outbound

This paper cites A survey of multimodal-guided image editing with text-to-image diffusion models.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection A survey of multimodal-guided image editing with text-to-image diffusion models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:20.340012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b01d790d-4ea1-491d-8f50-aee55a0a379c · outbound

This paper cites Mvss-net: Multi-view multi-scale supervised networks for image manipulation detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Mvss-net: Multi-view multi-scale supervised networks for image manipulation detection

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:20.436043Z

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Observation 035dba82-9f78-4d21-b85c-f8b6de937858 · outbound

This paper cites Simulating the real world: A unified survey of multimodal generative models.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Simulating the real world: A unified survey of multimodal generative models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:20.516620Z

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Observation baf75b04-94ae-4970-9df6-9b508883bb72 · outbound

This paper cites Free video-llm: Prompt-guided visual perception for efficient training-free video llms.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Free video-llm: Prompt-guided visual perception for efficient training-free video llms

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:20.653994Z

Source-reported events for the cited work

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Observation fb68164a-41aa-4691-917f-cc82bd947704 · outbound

This paper cites DF40: toward next-generation deepfake detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection DF40: toward next-generation deepfake detection

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:20.792023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 024ba99f-f924-44ca-8632-3b39b1723d01 · outbound

This paper cites Diffusion deepfake.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Diffusion deepfake

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:20.916465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a027ca1d-7b17-41a1-b8c8-e66b18b129f3 · outbound

This paper cites Genimage: A million-scale benchmark for detecting ai-generated image.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Genimage: A million-scale benchmark for detecting ai-generated image

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:21.073240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e9740c6-8e98-4be0-accb-d5fa6eadd03f · outbound

This paper cites On the detection of synthetic images generated by diffusion models.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection On the detection of synthetic images generated by diffusion models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:21.177237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c37f753-a948-440f-a3a6-6f28db357512 · outbound

This paper cites Rich and poor texture contrast: A simple yet effective approach for ai-generated image detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Rich and poor texture contrast: A simple yet effective approach for ai-generated image detection

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:21.399656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ba4bc3d-d51f-4fca-8e60-bc45535d2579 · outbound

This paper cites Bernstein, Alexander C.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Bernstein, Alexander C

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:21.570831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93e59458-bbbf-40de-8105-9271a9c35467 · outbound

This paper cites Ai-generated faces in the real world: A large-scale case study of twitter profile images.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Ai-generated faces in the real world: A large-scale case study of twitter profile images

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:21.760067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72d911b4-8504-4fbc-b657-1b0e5bbad4e1 · outbound

This paper cites an unresolved cited work.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:21.934531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c41bda36-0a02-4372-b88b-5b36a4ba87b9 · outbound

This paper cites Synbody: Synthetic dataset with layered human models for 3d human perception and modeling.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Synbody: Synthetic dataset with layered human models for 3d human perception and modeling

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:22.075979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 602d14c5-2e2f-4492-9b83-fd1931aa02d7 · outbound

This paper cites Cnn-generated images are surprisingly easy to spot...for now.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Cnn-generated images are surprisingly easy to spot...for now

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:22.189521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e55cfb4d-3109-420a-9ed4-ee3f363e4a0d · outbound

This paper cites SIDA: social media image deepfake detection, localization and explanation with large multimodal model.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection SIDA: social media image deepfake detection, localization and explanation with large multimodal model

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:22.358243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4e10598-ad20-45b4-b301-68e35e6c9735 · outbound

This paper cites Truefake: A real world case dataset of last generation fake images also shared on social networks, 2025.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Truefake: A real world case dataset of last generation fake images also shared on social networks, 2025

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:22.479652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b105348-f43b-4aaa-a74f-57519b3a2215 · outbound

This paper cites Deepfakebench: A comprehensive benchmark of deepfake detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Deepfakebench: A comprehensive benchmark of deepfake detection

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:22.639908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c455d7b-97a7-4b69-a3d6-dd0680580e2d · outbound

This paper cites Deepfake detection of face images based on a convolutional neural network.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Deepfake detection of face images based on a convolutional neural network

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:22.819708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7164ff42-693e-43de-8e15-b8f6bd0ce8e5 · outbound

This paper cites Hierarchical fine-grained image forgery detection and localization.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Hierarchical fine-grained image forgery detection and localization

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:22.942397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73c4fd8f-01a3-4640-8191-5ebd6286f268 · outbound

This paper cites Common sense reasoning for deepfake detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Common sense reasoning for deepfake detection

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:23.096910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fa97ec6-37a2-4571-a558-da691d002bd2 · outbound

This paper cites Fakeshield: Explainable image forgery detection and localization via multi-modal large language models.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Fakeshield: Explainable image forgery detection and localization via multi-modal large language models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:23.289110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0c325f4-9a82-4a7b-a771-90d0ea01e754 · outbound

This paper cites Onchis, and Radu Tudor Ionescu.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Onchis, and Radu Tudor Ionescu

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:23.478743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5e7ab0e-5af3-4e1a-888e-ded8e688957c · outbound

This paper cites Memory-space visual prompting for efficient vision-language fine-tuning.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Memory-space visual prompting for efficient vision-language fine-tuning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:23.654336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d3d4364-f3c7-4d10-bb9a-afa3c8252fb6 · outbound

This paper cites Eve: Efficient multimodal vision language models with elastic visual experts.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Eve: Efficient multimodal vision language models with elastic visual experts

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:23.858300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f2c2f1a-ee3d-45af-80af-a2e13ee80a19 · outbound

This paper cites an unresolved cited work.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:24.082007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d83493d-e57e-495d-9284-ef489473a167 · outbound

This paper cites DGPO: discovering multiple strategies with diversity-guided policy optimization.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection DGPO: discovering multiple strategies with diversity-guided policy optimization

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:24.243928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14f2c463-b782-4fa9-93d9-ee7fbfbfbe4b · outbound

This paper cites Alphamaze: Enhancing large language models' spatial intelligence via GRPO.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Alphamaze: Enhancing large language models' spatial intelligence via GRPO

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:24.358187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d112b07-8085-43f6-a46d-01fa2c981445 · outbound

This paper cites Voicegrpo: Modern moe transformers with group relative policy optimization GRPO for AI voice health care applications on voice pathology detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Voicegrpo: Modern moe transformers with group relative policy optimization GRPO for AI voice health care applications on voice pathology detection

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:24.467693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6db15794-481f-461a-bc5c-e025f78a6d38 · outbound

This paper cites Bird and Ahmad Lotfi.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Bird and Ahmad Lotfi

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:24.572819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfda08f0-0775-48de-a65b-1a32c27eeab7 · outbound

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

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection High-resolution image synthesis with latent diffusion models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:24.723446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 783d99dd-0236-41e8-863f-55c21d3b81a5 · outbound

This paper cites DE-FAKE: detection and attribution of fake images generated by text-to-image generation models.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection DE-FAKE: detection and attribution of fake images generated by text-to-image generation models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:24.872882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d206a127-0161-48ab-b08d-a91b3a0bf8b0 · outbound

This paper cites Hierarchical text-conditional image generation with CLIP latents.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Hierarchical text-conditional image generation with CLIP latents

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:25.023345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1726df4f-1209-46a2-85ca-a470b143f2b6 · outbound

This paper cites IMD2020: A large-scale annotated dataset tailored for detecting manipulated images.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection IMD2020: A large-scale annotated dataset tailored for detecting manipulated images

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:25.114757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a91f21fd-734e-4b3d-b615-d5c42eef385b · outbound

This paper cites Semantic image synthesis with spatially-adaptive normalization.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Semantic image synthesis with spatially-adaptive normalization

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:25.250140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70db215f-c6dd-47bd-a869-7f7b5505b94f · outbound

This paper cites Artifact: A large-scale dataset with artificial and factual images for generalizable and robust synthetic image detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Artifact: A large-scale dataset with artificial and factual images for generalizable and robust synthetic image detection

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:25.410818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcffdec7-5a70-497e-ae0b-b0cdc685604a · outbound

This paper cites Lee, Jonathan Ho, Tim Salimans, David J.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Lee, Jonathan Ho, Tim Salimans, David J

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:25.540728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff6820e2-2cf5-4f45-99de-0129d4de5213 · outbound

This paper cites Wukong: A 100 million large-scale chinese cross-modal pre-training benchmark.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Wukong: A 100 million large-scale chinese cross-modal pre-training benchmark

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:25.624622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 619f1819-b6fe-4878-b38b-9fab600dead4 · outbound

This paper cites an unresolved cited work.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Unresolved cited work

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:25.755747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a35e464-8a6f-4202-abd2-6aace11e90c8 · outbound

This paper cites LEGION: learning to ground and explain for synthetic image detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection LEGION: learning to ground and explain for synthetic image detection

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:25.863246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad7557d4-d698-403e-8bbc-8892815f0f37 · outbound

This paper cites Spot the fake: Large multimodal model-based synthetic image detection with artifact explanation.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Spot the fake: Large multimodal model-based synthetic image detection with artifact explanation

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:25.958021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07bc9d3c-aaac-43f0-abf9-44466f2ba0a3 · outbound

This paper cites GPT-4 technical report.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection GPT-4 technical report

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:26.103194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52152d8d-0c08-4c29-8bcb-a13312bfd632 · outbound

This paper cites an unresolved cited work.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Unresolved cited work

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:26.186925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcc68a8c-756f-4195-a848-db0237373fcd · outbound

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

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Forgerynet: A versatile benchmark for comprehensive forgery analysis

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:26.277829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 488ff476-d75d-4aad-abe8-49ddab4004a1 · outbound

This paper cites Faceforensics++: Learning to detect manipulated facial images.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Faceforensics++: Learning to detect manipulated facial images

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:26.377851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 397c6081-baa3-4638-ba11-a4d7aa4c1218 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection A style-based generator architecture for generative adversarial networks

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:26.484122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6fe7156-e432-4232-88a9-c09cf256092d · outbound

This paper cites Analyzing and improving the image quality of stylegan.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Analyzing and improving the image quality of stylegan

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:26.598842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bed72d56-08bc-410e-ac72-14b05387a93e · outbound

This paper cites Alias-free generative adversarial networks.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Alias-free generative adversarial networks

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:26.675945Z

Source-reported events for the cited work

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Observation 9c9f87b6-bb61-4be8-a6bd-f6139664c1e2 · outbound

This paper cites Language-guided hierarchical fine-grained image forgery detection and localization.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Language-guided hierarchical fine-grained image forgery detection and localization

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:26.775186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c64badfd-0a7b-433d-a3f4-6d3a96124c69 · outbound

This paper cites Diffforensics: Leveraging diffusion prior to image forgery detection and localization.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Diffforensics: Leveraging diffusion prior to image forgery detection and localization

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:48.434239Z

Source-reported events for the cited work

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Observation 610a5e77-42d3-467b-b605-d156a2c0abaa · outbound

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

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Self-supervised learning of adversarial example: Towards good generalizations for deepfake detection

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:48.287205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f479870e-bd15-4761-87d2-5b27e12e1df6 · outbound

This paper cites Deepfake generation and detection: A benchmark and survey.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Deepfake generation and detection: A benchmark and survey

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:48.161980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 23ca4934-829a-4009-a445-f384223e5c55 · outbound

This paper cites Faceswapguard: Safeguarding facial privacy from deepfake threats through identity obfuscation.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Faceswapguard: Safeguarding facial privacy from deepfake threats through identity obfuscation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:47.993622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 864212a6-400f-4222-97d5-cea8de39bf65 · outbound

This paper cites Trufor: Leveraging all-round clues for trustworthy image forgery detection and localization.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Trufor: Leveraging all-round clues for trustworthy image forgery detection and localization

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:47.817800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 587023e3-27e1-45e9-9aef-c08b1431bb34 · outbound

This paper cites Perceptual artifacts localization for image synthesis tasks.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Perceptual artifacts localization for image synthesis tasks

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:47.627002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 091afbb2-5031-4eeb-a08d-789920a36136 · outbound

This paper cites Pscc-net: Progressive spatio-channel correlation network for image manipulation detection and localization.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Pscc-net: Progressive spatio-channel correlation network for image manipulation detection and localization

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:47.479555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e73fa4f5-19ba-46a0-a151-0f3e148f4abc · outbound

This paper cites Fakediffer: Distributional disparity learning on differentiated reconstruction for face forgery detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Fakediffer: Distributional disparity learning on differentiated reconstruction for face forgery detection

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:47.356883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 700a8e27-9eb3-4aa6-8853-cef2a7c0f4ea · outbound

This paper cites Poisoned forgery face: Towards backdoor attacks on face forgery detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Poisoned forgery face: Towards backdoor attacks on face forgery detection

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:47.200006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7f736ac8-c8c1-4c3d-ac4e-a5742beceec8 · outbound

This paper cites Visual instruction tuning.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Visual instruction tuning

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:47.072688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8ab4fd04-fe04-4300-93c6-762f3277f5a8 · outbound

This paper cites Sa2va: Marrying sam2 with llava for dense grounded understanding of images and videos.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Sa2va: Marrying sam2 with llava for dense grounded understanding of images and videos

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:46.914870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e06e4347-a207-4d50-9529-cd586e2d9da0 · outbound

This paper cites Sa2va: Marrying sam2 with llava for dense grounded understanding of images and videos.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Sa2va: Marrying sam2 with llava for dense grounded understanding of images and videos

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:46.709677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2ae504fa-30de-4c56-9cd5-60589b68d9dd · outbound

This paper cites Omg-llava: Bridging image-level, object-level, pixel-level reasoning and understanding.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Omg-llava: Bridging image-level, object-level, pixel-level reasoning and understanding

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:46.514342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 89a8d08f-2d12-4bce-8329-373dfbfd0b7b · outbound

This paper cites Omg-seg: Is one model good enough for all segmentation? In CVPR , 2024.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Omg-seg: Is one model good enough for all segmentation? In CVPR , 2024

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:46.311089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b9ed2acb-dbbf-49ce-afdc-3fa5bc6d002f · outbound

This paper cites Forgerygpt: Multimodal large language model for explainable image forgery detection and localization.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Forgerygpt: Multimodal large language model for explainable image forgery detection and localization

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:46.075961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cb6e3d44-8b39-4731-b6e7-8f08e8aae317 · outbound

This paper cites Fakescope: Large multimodal expert model for transparent ai-generated image forensics.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Fakescope: Large multimodal expert model for transparent ai-generated image forensics

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:45.828730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8a2704c8-1590-496b-8425-43c6b6486c79 · outbound

This paper cites Riedmiller.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Riedmiller

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:45.576487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f039ad14-2f46-4938-9e81-4d299f4ab46f · outbound

This paper cites Proximal Policy Optimization Algorithms.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Proximal Policy Optimization Algorithms

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:28.667889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1958b3d0-e377-4f70-935f-060f341419bd · outbound

This paper cites Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:28.785796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69bb7fca-b746-4d50-8690-7e7b11996537 · outbound

This paper cites Mixed-r1: Unified reward perspective for reasoning capability in multimodal large language models.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Mixed-r1: Unified reward perspective for reasoning capability in multimodal large language models

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:45.394166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1266b2c9-22cc-4853-9ecc-9600eb987999 · outbound

This paper cites Seg-zero: Reasoning-chain guided segmentation via cognitive reinforcement.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Seg-zero: Reasoning-chain guided segmentation via cognitive reinforcement

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:45.222131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5096d69e-c953-433c-a591-ef85e7448798 · outbound

This paper cites Visual-rft: Visual reinforcement fine-tuning.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Visual-rft: Visual reinforcement fine-tuning

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:45.021544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7c15721f-8a9f-49cc-8cf6-5d7bc37b4d9f · outbound

This paper cites Vlm-r1: A stable and generalizable r1-style large vision-language model, 2025.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Vlm-r1: A stable and generalizable r1-style large vision-language model, 2025

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:44.754762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9ebeb7f0-69aa-45c9-96c5-e624eb22ad25 · outbound

This paper cites Midourney.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Midourney

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:44.551084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e4806350-eab6-4455-8082-2fcc555a1f6d · outbound

This paper cites DALL E 3.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection DALL E 3

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:44.301555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 568625b8-2448-4f05-99a6-754e0b0cba3a · outbound

This paper cites Jain, and Xiaoming Liu.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Jain, and Xiaoming Liu

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:44.038520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation af7915a7-2dc7-46f0-bcdc-5a121355dce8 · outbound

This paper cites Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll \' a r, and C.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll \' a r, and C

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:43.825977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 483a9d49-5a2f-42ef-99f1-5a0d9b4a7f47 · outbound

This paper cites Plummer, Liwei Wang, Chris M.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Plummer, Liwei Wang, Chris M

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:43.622596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ca89103f-f362-4841-9cd9-c4f7706f9a77 · outbound

This paper cites From colouring-in to pointillism: revisiting semantic segmentation supervision.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection From colouring-in to pointillism: revisiting semantic segmentation supervision

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:43.417471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1ecccd13-ec94-42db-89ae-b060dec89bf3 · outbound

This paper cites Recognize complex events from static images by fusing deep channels.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Recognize complex events from static images by fusing deep channels

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:43.249239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c76b72c9-b1e3-4f12-b69e-9bcdeba72c4b · outbound

This paper cites Deep learning face attributes in the wild.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Deep learning face attributes in the wild

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:43.029741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 28357705-1ad4-48b3-9c27-ab946823e70b · outbound

This paper cites Nguyen, Junichi Yamagishi, and Isao Echizen.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Nguyen, Junichi Yamagishi, and Isao Echizen

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:42.820561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 64c28f50-9607-40b2-8543-dd712e0e2142 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection A style-based generator architecture for generative adversarial networks

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:42.643213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e431df57-3091-4850-9ecf-7d6fdd4ff850 · outbound

This paper cites Qwen2.5-vl technical report.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Qwen2.5-vl technical report

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:42.462217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6c0b8255-8044-4793-bf37-3ea93f4a6dc9 · outbound

This paper cites Deep residual learning for image recognition.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Deep residual learning for image recognition

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:42.318577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4255fc32-3807-4b49-8ae9-72e69f18d75b · outbound

This paper cites SDXL: improving latent diffusion models for high-resolution image synthesis.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection SDXL: improving latent diffusion models for high-resolution image synthesis

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:42.138573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 392b9b31-ab44-45a9-b461-bec80f6aee03 · outbound

This paper cites Ideogram3.0.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Ideogram3.0

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:42.023658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1f752017-c284-4a42-81af-6fc9fb57c82d · outbound

This paper cites an unresolved cited work.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Unresolved cited work

Reference 86

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:31:41.834129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8da629c7-853e-44ba-8afd-76ffc37ee74a · outbound

This paper cites Lang-segment-anything, 2024.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Lang-segment-anything, 2024

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:41.669708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e4089302-d189-4f52-93b6-577d5c04896e · outbound

This paper cites Girshick, Piotr Doll \' a r, and Christoph Feichtenhofer.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Girshick, Piotr Doll \' a r, and Christoph Feichtenhofer

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:41.530436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 29f4cbd9-7f8b-4102-b64e-6c2585243138 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen - Zhu, Yuanzhi Li, Shean Wang, and Weizhu Chen.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen - Zhu, Yuanzhi Li, Shean Wang, and Weizhu Chen

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:41.332084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7c0c9735-e1f3-4f6a-b1c9-e35847bb65da · outbound

This paper cites an unresolved cited work.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Unresolved cited work

Reference 90

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:31:41.153170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ceedd368-59f4-452e-adc4-e261a20dfcb5 · outbound

This paper cites [RE] cnn-generated images are surprisingly easy to spot...for now.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection [RE] cnn-generated images are surprisingly easy to spot...for now

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:40.974871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f5b868c8-0b1f-4404-9380-167af071eb40 · outbound

This paper cites DIRE for diffusion-generated image detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection DIRE for diffusion-generated image detection

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:40.820145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f5ab5558-d112-47fb-8794-fdc7e4c267be · outbound

This paper cites Internvl3: Exploring advanced training and test-time recipes for open-source multimodal models, 2025.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Internvl3: Exploring advanced training and test-time recipes for open-source multimodal models, 2025

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-07T14:31:31.628673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e51df303-3610-40aa-82d4-f81c6e56be8e · outbound

This paper cites Towards universal fake image detectors that generalize across generative models.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Towards universal fake image detectors that generalize across generative models

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:40.634631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 744c221f-5b35-48c9-8787-97289a3001ac · outbound

This paper cites Frequency-aware deepfake detection: Improving generalizability through frequency space domain learning.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Frequency-aware deepfake detection: Improving generalizability through frequency space domain learning

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:40.453271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 303b3010-85b8-4501-9db1-77dc69f7bc74 · outbound

This paper cites Learning on gradients: Generalized artifacts representation for gan-generated images detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Learning on gradients: Generalized artifacts representation for gan-generated images detection

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:40.289618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d708f5bc-aeaf-40d9-b626-9c8317e91de7 · outbound

This paper cites Rethinking the up-sampling operations in cnn-based generative network for generalizable deepfake detection.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Rethinking the up-sampling operations in cnn-based generative network for generalizable deepfake detection

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:40.143945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ef742ab4-5377-400a-b97a-7331ee219756 · outbound

This paper cites Llama: Open and efficient foundation language models.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Llama: Open and efficient foundation language models

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:40.007085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d5416180-ac4c-4ac0-ba4e-dd489e135070 · outbound

This paper cites LISA: reasoning segmentation via large language model.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection LISA: reasoning segmentation via large language model

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:31:39.864968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 40a32399-b7b6-445f-acd7-792f9258437d · outbound

This paper cites an unresolved cited work.

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection Unresolved cited work

Reference 100

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:31:39.690030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation 217e49d4-8582-4c88-8461-5989aaaf39e2 · inbound

Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection cites this paper.

Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-08-03T03:15:17.929242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f721daea-35ed-41b4-a7c3-054b49034026 · inbound

Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection cites this paper.

Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T15:38:27.960723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6d8e8c8-96c9-4218-ab28-4ffe96b05480 · inbound

HEDGE: Heterogeneous Ensemble for Detection of AI-GEnerated Images in the Wild cites this paper.

HEDGE: Heterogeneous Ensemble for Detection of AI-GEnerated Images in the Wild So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-08-03T03:15:17.929242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2cfa802f-b53b-4e58-b275-c476e5085c20 · inbound

NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild cites this paper.

NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-08-03T03:15:17.929242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0e011906-24bf-4ca6-94b3-515c1663b51f · inbound

Boosting Robust AIGI Detection with LoRA-based Pairwise Training cites this paper.

Boosting Robust AIGI Detection with LoRA-based Pairwise Training So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-08-03T03:15:17.929242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3e24bae1-7292-425f-a251-c0663cb8c67b · inbound

Omni-Fake: Benchmarking Unified Multimodal Social Media Deepfake Detection cites this paper.

Omni-Fake: Benchmarking Unified Multimodal Social Media Deepfake Detection So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-08-03T03:15:17.929242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fc7b5fb6-c8ea-4a83-a14f-8b29cddc0183 · inbound

ReAlign: Generalizable Image Forgery Detection via Reasoning-Aligned Representation cites this paper.

ReAlign: Generalizable Image Forgery Detection via Reasoning-Aligned Representation So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-08-03T03:15:17.929242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b9e523b4-7104-4c35-9c88-a19e89f8a31d · inbound

JECA^2: Judgment-Explanation Consistent Adversarial Attack against Forensic Vision-Language Models cites this paper.

JECA^2: Judgment-Explanation Consistent Adversarial Attack against Forensic Vision-Language Models So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-08-03T03:15:17.929242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 053141ef-af96-4d27-bba0-fb12c75fbb3f · inbound

FakeVLM-R1: Internalizing Physical Laws via CoT for Synthetic Image Detection cites this paper.

FakeVLM-R1: Internalizing Physical Laws via CoT for Synthetic Image Detection So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-08-03T03:15:17.929242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 59d12d13-1d9f-4466-b10a-8e77d66ed894 · inbound

The Regularizing Power of Language-Training Deepfake Detectors cites this paper.

The Regularizing Power of Language-Training Deepfake Detectors So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-08-03T03:15:17.929242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4dd798a1-9fc8-4cda-a4d4-4b6067e77d02 · inbound

Face-Trace: Open-Set Attribution and Progressive Discovery of Synthetic Face Generators cites this paper.

Face-Trace: Open-Set Attribution and Progressive Discovery of Synthetic Face Generators So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-08-03T03:15:17.929242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.