Learning Counterfactually Decoupled Attention for Open-World Model Attribution | Paper Citation Record

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This paper cites com / iperov / DeepFaceLab.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution com / iperov / DeepFaceLab

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This paper cites com / deepfakes / faceswap.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution com / deepfakes / faceswap

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This paper cites SiT: Self-supervised vIsion Transformer.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution SiT: Self-supervised vIsion Transformer

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This paper cites Repmix: Represen- tation mixing for robust attribution of synthesized images.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Repmix: Represen- tation mixing for robust attribution of synthesized images

Reference 4

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This paper cites Open-world semi-supervised learning.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Open-world semi-supervised learning

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This paper cites Stargan: Unified genera- tive adversarial networks for multi-domain image-to-image translation.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Stargan: Unified genera- tive adversarial networks for multi-domain image-to-image translation

Reference 6

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

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Xception: Deep learning with depthwise separable convolutions

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This paper cites On the detection of digital face manipulation.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution On the detection of digital face manipulation

Reference 8

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This paper cites Arcface: Additive angular margin loss for deep face recognition.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Arcface: Additive angular margin loss for deep face recognition

Reference 9

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This paper cites Reducing network agnostophobia.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Reducing network agnostophobia

Reference 10

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This paper cites Diffusion mod- els beat gans on image synthesis.NeurIPS, 34:8780–8794,.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Diffusion mod- els beat gans on image synthesis.NeurIPS, 34:8780–8794,

Reference 11

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This paper cites Taming transformers for high-resolution image synthesis.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Taming transformers for high-resolution image synthesis

Reference 12

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This paper cites Leveraging fre- quency analysis for deep fake image recognition.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Leveraging fre- quency analysis for deep fake image recognition

Reference 13

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This paper cites Towards discovery and attribution of open-world gan generated images.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Towards discovery and attribution of open-world gan generated images

Reference 14

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This paper cites Generative adversarial nets.NeurIPS, 27,.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Generative adversarial nets.NeurIPS, 27,

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This paper cites On the exploitation of deepfake model recognition.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution On the exploitation of deepfake model recognition

Reference 16

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This paper cites Robust semi-supervised learning when not all classes have labels.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Robust semi-supervised learning when not all classes have labels

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This paper cites Automatically discov- ering and learning new visual categories with ranking statis- tics.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Automatically discov- ering and learning new visual categories with ranking statis- tics

Reference 18

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This paper cites Ghostnet: More features from cheap opera- tions.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Ghostnet: More features from cheap opera- tions

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

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Forgerynet: A versatile benchmark for comprehensive forgery analysis

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This paper cites Denoising dif- fusion probabilistic models.NeurIPS, 33:6840–6851, 2020.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Denoising dif- fusion probabilistic models.NeurIPS, 33:6840–6851, 2020

Reference 21

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This paper cites Pfa-gan: Progressive face aging with gen- erative adversarial network.TIFS, 16:2031–2045, 2020.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Pfa-gan: Progressive face aging with gen- erative adversarial network.TIFS, 16:2031–2045, 2020

Reference 22

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This paper cites Sc-fegan: Face editing gen- erative adversarial network with user’s sketch and color.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Sc-fegan: Face editing gen- erative adversarial network with user’s sketch and color

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This paper cites Towards open world object de- tection.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Towards open world object de- tection

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This paper cites Progressive growing of gans for improved quality, stability, and variation.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Progressive growing of gans for improved quality, stability, and variation

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

Learning Counterfactually Decoupled Attention for Open-World Model Attribution A style-based generator architecture for generative adversarial networks

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This paper cites Decentralized attribution of generative models.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Decentralized attribution of generative models

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This paper cites Auto-encoding varia- tional bayes.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Auto-encoding varia- tional bayes

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This paper cites The hungarian method for the assignment problem.NRL, 2(1-2):83–97, 1955.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution The hungarian method for the assignment problem.NRL, 2(1-2):83–97, 1955

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This paper cites Are handcrafted filters helpful for attributing ai-generated images? InACM MM, pages 10698–10706, 2024.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Are handcrafted filters helpful for attributing ai-generated images? InACM MM, pages 10698–10706, 2024

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This paper cites FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping

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This paper cites Face x-ray for more general face forgery detection.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Face x-ray for more general face forgery detection

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This paper cites Counterfactual intervention feature transfer for visible- infrared person re-identification.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Counterfactual intervention feature transfer for visible- infrared person re-identification

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

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Celeb-df: A large-scale challenging dataset for deep- fake forensics

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This paper cites Detecting generated images by real images.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Detecting generated images by real images

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This paper cites Which model generated this image? a model- agnostic approach for origin attribution.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Which model generated this image? a model- agnostic approach for origin attribution

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This paper cites Residual denoising diffu- sion models.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Residual denoising diffu- sion models

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This paper cites Discovering causal signals in images.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Discovering causal signals in images

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This paper cites Do gans leave artificial fingerprints? In MIPR, pages 506–511, 2019.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Do gans leave artificial fingerprints? In MIPR, pages 506–511, 2019

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This paper cites Causality: models, reasoning, and inference, by judea pearl, cambridge university press, 2000.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Causality: models, reasoning, and inference, by judea pearl, cambridge university press, 2000

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This paper cites FSGAN: Subject agnostic face swapping and reenactment.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution FSGAN: Subject agnostic face swapping and reenactment

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This paper cites Towards uni- versal fake image detectors that generalize across generative models.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Towards uni- versal fake image detectors that generalize across generative models

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This paper cites Basic books, 2018.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Basic books, 2018

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This paper cites Scalable diffusion models with transformers.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Scalable diffusion models with transformers

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This paper cites Counterfactual attention learning for fine-grained visual cat- egorization and re-identification.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Counterfactual attention learning for fine-grained visual cat- egorization and re-identification

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This paper cites Openldn: Learn- ing to discover novel classes for open-world semi-supervised learning.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Openldn: Learn- ing to discover novel classes for open-world semi-supervised learning

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

Learning Counterfactually Decoupled Attention for Open-World Model Attribution High-resolution image syn- thesis with latent diffusion models

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

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Faceforen- sics++: Learning to detect manipulated facial images

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This paper cites Open-world semantic segmen- tation including class similarity.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Open-world semantic segmen- tation including class similarity

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This paper cites Learning structured output representation using deep conditional gen- erative models.NeurIPS, 28, 2015.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Learning structured output representation using deep conditional gen- erative models.NeurIPS, 28, 2015

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Observation ea1202a9-ecee-41d1-814e-dcb7f2877e72 · outbound

This paper cites Denois- ing diffusion implicit models.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Denois- ing diffusion implicit models

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This paper cites Contrastive pseudo learning for open-world deepfake attribution.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Contrastive pseudo learning for open-world deepfake attribution

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:17.937995Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 59ea4e36-c2fd-4261-8c30-8be590bbc011 · outbound

This paper cites Rethinking open-world deepfake attribution with multi-perspective sensory learning.IJCV, pages 1–24, 2024.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Rethinking open-world deepfake attribution with multi-perspective sensory learning.IJCV, pages 1–24, 2024

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:17.731117Z

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Observation c938b217-3469-4bf8-9a50-ffabab114419 · outbound

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

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Rethinking the up-sampling operations in cnn-based generative network for generalizable deepfake detection

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:17.566950Z

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Observation e80b36b7-3a71-4c5a-9c9d-a2657060a51a · outbound

This paper cites Visual autoregressive modeling: Scalable image gen- eration via next-scale prediction.NeurIPS, 37:84839–84865,.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Visual autoregressive modeling: Scalable image gen- eration via next-scale prediction.NeurIPS, 37:84839–84865,

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Resolution: unresolved; no resolver link, observed 2026-08-06T21:55:13.149053Z

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Observation 552b7148-a6c2-4fdd-a68c-2bbd2cd8e22a · outbound

This paper cites Neural discrete representation learning.NeurIPS, 30, 2017.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Neural discrete representation learning.NeurIPS, 30, 2017

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:17.415606Z

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Observation 26e8ac1a-b090-416f-8079-854eb9e4a968 · outbound

This paper cites Visualizing data using t-sne.JMLR, 9(11), 2008.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Visualizing data using t-sne.JMLR, 9(11), 2008

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:17.257153Z

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Observation fbebfaa2-ec00-4a38-aa9f-171b0a11f7c6 · outbound

This paper cites Counterfactual cycle-consistent learn- ing for instruction following and generation in vision- language navigation.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Counterfactual cycle-consistent learn- ing for instruction following and generation in vision- language navigation

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:17.078694Z

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Observation 900e01a2-113b-47fb-939d-d4362dc21be6 · outbound

This paper cites Visual commonsense r-cnn.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Visual commonsense r-cnn

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:16.940208Z

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Observation 8bab137c-1d08-4f7a-95f2-ce462237c184 · outbound

This paper cites Forgerynir: deep face forgery and detec- tion in near-infrared scenario.TIFS, 17:500–515, 2022.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Forgerynir: deep face forgery and detec- tion in near-infrared scenario.TIFS, 17:500–515, 2022

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:16.848460Z

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Observation 1a60cbe8-bc21-4392-a341-5493a1bc9189 · outbound

This paper cites Where did i come from? origin attribution of ai-generated images.NeurIPS, 36:74478–74500, 2023.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Where did i come from? origin attribution of ai-generated images.NeurIPS, 36:74478–74500, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:16.740725Z

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Observation 16ed33a6-fedd-4692-a208-5bbdac6bc124 · outbound

This paper cites Df40: Toward next- generation deepfake detection.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Df40: Toward next- generation deepfake detection

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:16.625404Z

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Observation 7ed28e9c-fa3b-45f0-9906-c9647bbef336 · outbound

This paper cites Deepfake network architecture attribution.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Deepfake network architecture attribution

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:16.476964Z

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Observation 23a6dd3f-0bfd-41db-a9bd-f45daf544866 · outbound

This paper cites Progressive open space expan- sion for open-set model attribution.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Progressive open space expan- sion for open-set model attribution

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:16.322672Z

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Observation 2ce0d751-cfa1-4454-9237-cc0d539c062b · outbound

This paper cites Attributing fake images to gans: Learning and analyzing gan fingerprints.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Attributing fake images to gans: Learning and analyzing gan fingerprints

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:16.172747Z

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Observation 6df55b51-aa8d-46ca-9699-1b47a3dc5465 · outbound

This paper cites Artificial fingerprinting for generative models: Root- ing deepfake attribution in training data.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Artificial fingerprinting for generative models: Root- ing deepfake attribution in training data

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:16.007678Z

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Observation 486bbc4e-5b23-400e-94ed-a67ec7c030c2 · outbound

This paper cites Responsible disclosure of generative mod- els using scalable fingerprinting.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Responsible disclosure of generative mod- els using scalable fingerprinting

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:15.793022Z

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Observation 4dd8794e-93e2-4960-b9a5-bc0e52cc2821 · outbound

This paper cites Counterfactual zero-shot and open-set vi- sual recognition.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Counterfactual zero-shot and open-set vi- sual recognition

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:15.565784Z

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Observation 0b9a64ba-fcb7-45de-a8ca-bf61e04d5113 · outbound

This paper cites Multi-attentional deep- fake detection.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Multi-attentional deep- fake detection

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:15.405026Z

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Observation 906f820d-1e5e-4e31-b269-269edbdf9da7 · outbound

This paper cites Learning deep features for discrimi- native localization.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Learning deep features for discrimi- native localization

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:15.187063Z

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Observation 6285a43a-c464-486b-bf44-e4001fdf06db · outbound

This paper cites Unpaired image-to-image translation using cycle- consistent adversarial networkss.

Learning Counterfactually Decoupled Attention for Open-World Model Attribution Unpaired image-to-image translation using cycle- consistent adversarial networkss

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:55:14.915457Z

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