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Paper Citation Record · LEDGER

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS

As of 21 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2507.22880.

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

pith.paper-citation-record.v1
2507.22880 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:16:50.266362Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

51 of 51 outbound references displayed

  • verified exact2
  • verified fuzzy34
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 25ab7059-decf-4c0d-b263-83ab1d2b020b · outbound

This paper cites Deep neural networks for youtube recommendations.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Deep neural networks for youtube recommendations

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f4bcaf12-f721-4a86-9c8a-3ec68b77f326 · outbound

This paper cites Parameter-efficient transfer from sequential behaviors for user modeling and recommendation.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Parameter-efficient transfer from sequential behaviors for user modeling and recommendation

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-06T11:16:58.070142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 39255b05-381e-4829-87a1-d996a8310fbd · outbound

This paper cites Matrix factorization techniques for recommender systems.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Matrix factorization techniques for recommender systems

Reference 3

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no resolver link, observed 2026-08-06T11:16:45.584007Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:45.584007Z digest=sha256:d5273b3e5a055625e4e75881dde54b4cf3ffa8a629cdecc8ccdaf56e4999bfea

Observation de8e6342-9544-46a6-b027-86a22f758226 · outbound

This paper cites A review of modern fashion recommender systems.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS A review of modern fashion recommender systems

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-06T11:16:57.893834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:45.703280Z digest=sha256:ff5d4d2ce84183e1c24ecb0fc369a5469bc6b55752b04878908d8083797023e9

Observation 6ee81ede-e003-43ff-9864-a8bfad5d7d98 · outbound

This paper cites Vbpr: visual bayesian personalized ranking from implicit feedback.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Vbpr: visual bayesian personalized ranking from implicit feedback

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:57.675837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:45.772964Z digest=sha256:3cd13a21014ada3cf61412fc663085b4982d8fe6ffeeb4cde726656ac5eb1657

Observation b47edd31-aa8b-4469-8a4d-bae4408bd57b · outbound

This paper cites Aesthetic-based clothing recommen- dation.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Aesthetic-based clothing recommen- dation

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:57.467235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:45.832176Z digest=sha256:3bb2773a82d91be986bc5085df1191821e105f32a35b94a02e2443e04a95d209

Observation 1ef73e13-96df-4264-a6f0-b9a86925df63 · outbound

This paper cites Attacking visually-aware recommender systems with transferable and imperceptible adversarial styles.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Attacking visually-aware recommender systems with transferable and imperceptible adversarial styles

Reference 7

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raw_fallback, observed 2026-08-06T11:16:57.264470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:45.959924Z digest=sha256:edc60e0a0683c97c180586b287bf866cb3d31958eb2adc1a0090653168f2fa36

Observation 9e161301-2593-4daf-97f0-7623fca03268 · outbound

This paper cites Adversarial item promotion: Vulnerabilities at the core of top-n recommenders that use images to address cold start.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Adversarial item promotion: Vulnerabilities at the core of top-n recommenders that use images to address cold start

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:57.056808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:46.059346Z digest=sha256:996a824e11096183d954102641cd271eaf7611b0cb3703af31ea907607eecf9c

Observation c93816c3-de0a-477a-ac35-89a72ff7b55a · outbound

This paper cites Adversarial item promotion on visually-aware recommender systems by guided diffusion.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Adversarial item promotion on visually-aware recommender systems by guided diffusion

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-06T11:16:56.711056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:46.161406Z digest=sha256:ca6d0925d6acf16c2a927e6168b1ece8f6e7c3a92a706db823ad7fedd0fe485a

Observation 33b051a3-13e5-419c-87b7-be2a59cfd112 · outbound

This paper cites Attacking click-through rate predictors via generating realistic fake samples.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Attacking click-through rate predictors via generating realistic fake samples

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-06T11:16:56.432190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:46.250506Z digest=sha256:8068048223c53ad101635d0951e54753cbe1744b20b2075e8e58fbfee3d1b3cf

Observation 7c486ce9-205a-419a-80df-69ab4fd51863 · outbound

This paper cites ToDA: Target-oriented Diffusion Attacker against Recommendation System.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS ToDA: Target-oriented Diffusion Attacker against Recommendation System

Reference 11

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verified exact
local_arxiv, observed 2026-08-06T11:16:50.705655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:46.343963Z digest=sha256:024ce9c7fb238d23c14df2cbbca2bed20369c1a989b07d614e43a854457c6f26

Observation d40f76ad-649d-48f2-b033-a9b81f53c0d7 · outbound

This paper cites Adver- sarial attacks for black-box recommender systems via copying transferable cross-domain user profiles.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Adver- sarial attacks for black-box recommender systems via copying transferable cross-domain user profiles

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:56.084731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:46.445505Z digest=sha256:0f9d8c08d0527b944e12effeadf963eed8753dd51ab17a73cafbe04b8c2701e7

Observation 466701d3-28de-4032-b93a-f9ce45cbf84e · outbound

This paper cites Influence-driven data poisoning for robust recommender systems.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Influence-driven data poisoning for robust recommender systems

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-06T11:16:55.784120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:46.570837Z digest=sha256:16c5b7e42a1a6f0139700b1b54ef5b50056de358e330bdef144fb9a2a763d4fd

Observation d1f592b3-1ebf-4d6f-9816-3ed59c18c2bf · outbound

This paper cites Poisoning gnn-based recommender systems with generative surrogate-based attacks.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Poisoning gnn-based recommender systems with generative surrogate-based attacks

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:55.473351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:46.640840Z digest=sha256:e2bc5cb3a84ccadea643bc392841257597fec061d0b5cf6efbaa053c1140edf3

Observation 67bbb62f-374d-483c-9514-d5f537806279 · outbound

This paper cites Poisoning attacks to graph-based recommender systems.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Poisoning attacks to graph-based recommender systems

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:55.193122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:46.712797Z digest=sha256:c8408e4749fb2355dff681219f4d82c328d84aebf170a38528360a4e190a8ff1

Observation f768b4c0-edf8-478f-a6af-020e9aa87c8c · outbound

This paper cites Shilling attacks against recommender systems: a comprehensive survey.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Shilling attacks against recommender systems: a comprehensive survey

Reference 16

Resolution
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raw_fallback, observed 2026-08-06T11:16:54.911749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:46.797473Z digest=sha256:6e006bef0517d0bc4ead553ac508bfe4f65b4ca93518a8d568fe7e85abd6a69e

Observation 76f044b5-7a61-4638-ad68-824f3e7df69e · outbound

This paper cites Data Poisoning Attacks to Deep Learning Based Recommender Systems.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Data Poisoning Attacks to Deep Learning Based Recommender Systems

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:46.891644Z digest=sha256:7610c9738fab7af9d448039b9c5209eba075d54d2da442f25fdd4f07bb0f4c70

Observation 1217ca96-8b31-42f3-a68f-e653da634ede · outbound

This paper cites Triple adversarial learning for influence based poisoning attack in recommender systems.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Triple adversarial learning for influence based poisoning attack in recommender systems

Reference 18

Resolution
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raw_fallback, observed 2026-08-06T11:16:54.602995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:46.950771Z digest=sha256:912cca7c995b7a55ed7e10e4049dc5feeae6a4d9d4fd57578c3ac206bdca6405

Observation f9a559ec-783d-4ac7-9b79-0f40f3c6093a · outbound

This paper cites Fight fire with fire: Towards robust recommender systems via adversarial poisoning training.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Fight fire with fire: Towards robust recommender systems via adversarial poisoning training

Reference 19

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raw_fallback, observed 2026-08-06T11:16:54.331190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:47.048362Z digest=sha256:dd3fc16c3ed8963df7e09870d1d9d8bff7674000f76ab696e25d502a2ac06f97

Observation 63d23e66-d25b-41f3-bbbf-557b7d9825da · outbound

This paper cites Learning transferable visual models from natural language supervision.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Learning transferable visual models from natural language supervision

Reference 20

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no resolver link, observed 2026-08-06T11:16:47.153846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:47.153846Z digest=sha256:f9baedc5801e82e4ce76220c921416a6b89bbc0081a41828bf69a106cb8a8525

Observation 74882b88-1ba8-4e65-b218-1906d4061990 · outbound

This paper cites Towards Modality Generalization: A Benchmark and Prospective Analysis.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Towards Modality Generalization: A Benchmark and Prospective Analysis

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:47.229766Z digest=sha256:faa580a05bd559e63ca7a38cbbe676ba256fcbd08ad8235f194ed1bc7874a155

Observation dab34ed6-8805-4da7-8d5e-6ca1479f95fc · outbound

This paper cites Continual multimodal contrastive learning.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Continual multimodal contrastive learning

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:47.292336Z digest=sha256:565b1fce41e884f33eebabb7a0010dee94e082529ef123ec5fc5b1d9d8672d51

Observation 19053ec4-3610-4889-9ba7-492deba50ec7 · outbound

This paper cites Getting the look: clothing recognition and segmentation for automatic product suggestions in everyday photos.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Getting the look: clothing recognition and segmentation for automatic product suggestions in everyday photos

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-06T11:16:54.250541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:47.379669Z digest=sha256:7d6c8fe282b8570ce3c6018322daaa706ce051791132356c460d16a0624d6713

Observation bcdd39b5-4e7e-4860-a306-3420965b18e4 · outbound

This paper cites Large scale visual recommendations from street fashion images.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Large scale visual recommendations from street fashion images

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:54.172322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:47.490149Z digest=sha256:7e0db0de6448a83b7e774ed69237809b8100a9e3438f16f40ca96800bc5facac

Observation b68640bb-4e10-4218-b7cc-27e607d49494 · outbound

This paper cites Deep residual learning for image recognition.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Deep residual learning for image recognition

Reference 25

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no resolver link, observed 2026-08-06T11:16:47.593538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:47.593538Z digest=sha256:9ecd22b41e9ed709340d3b8162822f2dd723006f00041642c27127dae29885b0

Observation 16a95242-dcf5-4c99-8546-23a65bfe2cc8 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 26

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unresolved
no resolver link, observed 2026-08-06T11:16:47.691892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:47.691892Z digest=sha256:112e13efbe8042d94dc30fcd381e1c4277f692ffa5ce7be6f20f807e528b1af8

Observation 857864cc-fbda-4a8b-b44d-8197b3ac0cb1 · outbound

This paper cites BPR: Bayesian Personalized Ranking from Implicit Feedback.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS BPR: Bayesian Personalized Ranking from Implicit Feedback

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T11:16:47.798906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:47.798906Z digest=sha256:4ae5671984b305a6f811c12ce160dbdf648a1f319a7980f57ae24fdf7ef2ba2a

Observation 9eb1be45-2841-42f5-b35d-0b6a4da837b8 · outbound

This paper cites Neural collaborative filtering.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Neural collaborative filtering

Reference 28

Resolution
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no resolver link, observed 2026-08-06T11:16:47.873012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:47.873012Z digest=sha256:e5eeacc24c9d22f2a6cffd944d294aad382197ea4bddf78a7635dd5ce7da47d5

Observation fe38bba2-ba49-4617-8d66-04b20d5c820b · outbound

This paper cites Image-based recommendations on styles and substitutes.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Image-based recommendations on styles and substitutes

Reference 29

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unresolved
no resolver link, observed 2026-08-06T11:16:47.978960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:47.978960Z digest=sha256:15e9a970da859c9cb0e1b7d40f6ecb89559af6f48b071076b25bbbb486361ca8

Observation 8ace6b26-87bb-45c1-ba76-645a5292844b · outbound

This paper cites Elimrec: Eliminating single-modal bias in multimedia recommendation.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Elimrec: Eliminating single-modal bias in multimedia recommendation

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:53.983133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:48.094667Z digest=sha256:68009fa5ebd9bd391e48651ae6746c975a9af9abb9331bf269346a1d44f3596c

Observation 576adc62-6052-4d66-a079-04d3886e85e6 · outbound

This paper cites Self- supervised learning for multimedia recommendation.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Self- supervised learning for multimedia recommendation

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:53.844645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:48.234204Z digest=sha256:55102023b46a8c623a6afe1e853e6f3e59aeb2b563d13e597866883df5d6b82a

Observation f49754b8-0d48-4c85-a6da-ae016bb3de84 · outbound

This paper cites Fashion DNA: Merging Content and Sales Data for Recommendation and Article Mapping.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Fashion DNA: Merging Content and Sales Data for Recommendation and Article Mapping

Reference 32

Resolution
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no resolver link, observed 2026-08-06T11:16:48.389430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:48.389430Z digest=sha256:2bc40323e90d7362acbfb6113b3101bfb41bdfb5f91aa6b27dfca022bf43f18f

Observation 2ed45db6-70aa-47ec-9137-c68fd2544b22 · outbound

This paper cites Visually-aware fashion recommendation and design with generative image models.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Visually-aware fashion recommendation and design with generative image models

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:53.699164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:48.502354Z digest=sha256:fce25e12073788dd7d044efaa55e14c7d7e7bbf9003ef21c09e1cbe0e24622d7

Observation ebbdd369-ecba-4d83-b337-88f529bd0ffa · outbound

This paper cites Adversarial training towards robust multimedia recommender system.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Adversarial training towards robust multimedia recommender system

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:53.554169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:48.612572Z digest=sha256:50cfeadcebc36d0a8d98b90026a66c774e5d39eca40e1af313aa755ef9724362

Observation 14e98fe9-95ba-4573-ae65-df83cca7d0d2 · outbound

This paper cites Shilling black-box recommender systems by learning to generate fake user profiles.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Shilling black-box recommender systems by learning to generate fake user profiles

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:53.379562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:48.721190Z digest=sha256:903d21e41c7f9f70a0b14e3d04a5c3f41dbc433785ab889d2ca87e2c5741c5df

Observation c18d8b4f-b69f-4018-a0b5-5526f3763627 · outbound

This paper cites Diffcl: A diffusion-based contrastive learning framework with semantic alignment for multimodal recommendations.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Diffcl: A diffusion-based contrastive learning framework with semantic alignment for multimodal recommendations

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:53.209240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:48.823477Z digest=sha256:603136e4f84d9c10a90cdcf041f6af74b6205b052812465d983b93129a1b9eb8

Observation 9e07f615-0686-4030-8dae-87a520105577 · outbound

This paper cites Robust privacy-preserving recommendation systems driven by multimodal federated learning.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Robust privacy-preserving recommendation systems driven by multimodal federated learning

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:53.048905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:48.917556Z digest=sha256:fab59bc7d4fbf23d923ebee9b14d1002f0aaffc5b2aa635d15b0f39bca295a37

Observation a5b290cb-200e-44b0-97b8-bbbbe3599f44 · outbound

This paper cites A survey on federated recommendation systems.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS A survey on federated recommendation systems

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:52.885240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:48.999944Z digest=sha256:ec675a31284205727d39f7204e7d0d5380cbd701f0af01e0558814c787d9a000

Observation 82751c7f-0262-4b20-9832-17de95d591fe · outbound

This paper cites Multi-view graph convolutional network for multimedia recommendation.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Multi-view graph convolutional network for multimedia recommendation

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:52.726154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:49.109664Z digest=sha256:c820193e4740ad1f18f45f135d68ad04d52d61bf1fd801c27c3cec904a2147cd

Observation 15918c77-e0ea-4382-9e03-a949063522a3 · outbound

This paper cites Llmrec: Large language models with graph augmentation for recommendation.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Llmrec: Large language models with graph augmentation for recommendation

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:52.525380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:49.193548Z digest=sha256:27d8fb720f760792004312d1ba1d291615f6eb72e2a31d01d83f67cb6c2d6ea0

Observation 70efd63c-b4ce-4d52-b8fd-bfdc5a6db03a · outbound

This paper cites MENTOR: Multi-level Self-supervised Learning for Multimodal Recommendation.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS MENTOR: Multi-level Self-supervised Learning for Multimodal Recommendation

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-06T11:16:50.449731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:49.325773Z digest=sha256:0dfb67189b04356fd8f877844e1f14df06b7f30dce15bd7e28636b3a47c411b5

Observation 124a3fc3-6f2b-44f1-a085-a7d04be29517 · outbound

This paper cites Lightgcn: Simplifying and powering graph convolution network for recommendation.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Lightgcn: Simplifying and powering graph convolution network for recommendation

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:52.377936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:49.438203Z digest=sha256:8b5b1ad7c98f5175d0a6ae6d312513ff98289a2cba861365c470f3c02bea77d5

Observation 81387a84-740b-447c-b015-0e830b638f56 · outbound

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

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS High-resolution image synthesis with latent diffusion models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T11:16:49.520533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:16:49.520533Z digest=sha256:1d7e5583832953e8f4fa7c8d80100b0d08b6602f6ceabff5126da0574e51ba7c

Observation dace5166-cf05-495e-8efd-bed7511c5f6a · outbound

This paper cites Taamr: Targeted adversarial attack against multimedia recommender systems.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Taamr: Targeted adversarial attack against multimedia recommender systems

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:52.217977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:49.588917Z digest=sha256:8cbc67f36a847894e96ce335f766bc65b0a1639ba4d0f001d81c3b063afab2d5

Observation 2819c5f9-971d-4ced-8a31-3d78bcb0cdfa · outbound

This paper cites The youtube video recommendation system.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS The youtube video recommendation system

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:52.007990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:49.669948Z digest=sha256:90061fd3270f872ab2066d9140b38ac1cb0903453d38ca84d2214111f18cc02d

Observation 5f066f7f-d78b-483d-84ec-f67d0bb70664 · outbound

This paper cites Billion-scale commodity embedding for e-commerce recommendation in alibaba.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Billion-scale commodity embedding for e-commerce recommendation in alibaba

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:51.820030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:49.737598Z digest=sha256:092273f6f016438a37942ac31a111d4ca55df673122fb34cd2421c29c3aa948e

Observation 6d71f39b-c384-4114-bf6d-6b6b00d1d66d · outbound

This paper cites an unresolved cited work.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-06T11:16:51.625348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:49.864610Z digest=sha256:c55df9e7c455062e6cba3eefc1d16cad0b2a8019bf1ea6252b16b4d79d4727e7

Observation 87645ab7-6d69-4bbd-94b2-68c71e6ac8c3 · outbound

This paper cites an unresolved cited work.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-06T11:16:51.475949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:49.957271Z digest=sha256:52b9065772f01490b8cb85e2cb74121fba3fd58682b4d7b113654a9f1bdbdcec

Observation 2d38e8f6-b664-4d2b-9559-973e47ff7615 · outbound

This paper cites Detecting adversarial examples via reconstruction-based semantic inconsistency.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Detecting adversarial examples via reconstruction-based semantic inconsistency

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:51.320852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:50.049913Z digest=sha256:34441fa7698140e6b72ada209a61ec22fc83d32754ae827ceccca65ed7c774b1

Observation 9e9cf3f0-1c3f-4c32-9e66-c4188076a24d · outbound

This paper cites Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, and Dhruv Batra.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, and Dhruv Batra

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:51.110681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:50.139329Z digest=sha256:83887044c5d4772721ba1d24bbdcc62c7f45e87b251e9e439f66171d44157942

Observation fbf96a95-2d54-4b07-9e11-b4da548ed898 · outbound

This paper cites Adversarial examples are not bugs, they are features.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS Adversarial examples are not bugs, they are features

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:16:50.937533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T11:16:50.266362Z digest=sha256:2b185f8f359d8060c02fa2bf5b21041229f78c5594da47f83ffd65aa163cd6c4

Pith citing papers

No inbound Pith citation observations are available.