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Paper Citation Record · LEDGER

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions

As of 17 August 2026, this Paper Citation Record lists 100 of 218 outbound references and 0 inbound Pith citation observations for arXiv:2508.19620.

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

pith.paper-citation-record.v1
2508.19620 v1

Coverage vector

measured 100 of 218 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:41:00.608752Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

100 of 218 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved99
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aa299fae-4dda-46a7-b711-bb262f406ce7 · outbound

This paper cites Improved diversity-promoting collaborative metric learning for recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Improved diversity-promoting collaborative metric learning for recommendation,

Reference 1

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Observation 5c197bff-b568-43fc-9452-26503b6d6a99 · outbound

This paper cites Multimedia recommendation: technology and techniques,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Multimedia recommendation: technology and techniques,

Reference 4

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Observation db3ea0af-7778-4fbb-8c96-0c6bd3c49830 · outbound

This paper cites A survey on federated recommendation systems,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions A survey on federated recommendation systems,

Reference 5

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Observation 0b33ba2c-4d8b-48ba-980e-78fa7b4d5acb · outbound

This paper cites Hetefedrec: Federated recommender systems with model heterogeneity,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Hetefedrec: Federated recommender systems with model heterogeneity,

Reference 6

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Observation bbcfe833-4cf0-435f-82a9-e740c08504a2 · outbound

This paper cites No prejudice! fair federated graph neural networks for personalized recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions No prejudice! fair federated graph neural networks for personalized recommendation,

Reference 7

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Observation 254f8ce3-ac80-4476-8483-6ed6efcfbb99 · outbound

This paper cites Refrs: Resource-efficient federated recommender system for dynamic and diversified user preferences,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Refrs: Resource-efficient federated recommender system for dynamic and diversified user preferences,

Reference 8

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Observation 67c36f68-26a8-4f11-a9d9-83d89aade100 · outbound

This paper cites Meta matrix factorization for federated rating predictions,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Meta matrix factorization for federated rating predictions,

Reference 9

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source=pdf_text observed=2026-08-05T15:41:00.085801Z digest=sha256:4641a1cf345ee9be7355878f2ae099df49500121c8e9803847f3ea74ea497688

Observation d7a98177-15dd-41ec-acbd-9e0f3928db70 · outbound

This paper cites When federated recommendation meets cold-start problem: Separating item attributes and user interactions,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions When federated recommendation meets cold-start problem: Separating item attributes and user interactions,

Reference 10

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Observation 064bb1e4-46b7-48f4-a635-41b7c269a7cd · outbound

This paper cites Federated recommendation with additive personalization,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Federated recommendation with additive personalization,

Reference 11

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Observation db49337e-c513-4671-9018-dbd84099b97a · outbound

This paper cites Dual personalization on federated recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Dual personalization on federated recommendation,

Reference 12

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source=pdf_text observed=2026-08-05T15:41:00.099414Z digest=sha256:6eba826c1db50285791f829d7f725d67bff34844c818e5511d58640b46d3249e

Observation 58f73570-f512-4b33-aa82-62a592ad76a2 · outbound

This paper cites Gpfedrec: Graph-guided personalization for federated recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Gpfedrec: Graph-guided personalization for federated recommendation,

Reference 13

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Observation 293f8b18-513e-46c3-99f0-8b67c7dd6424 · outbound

This paper cites Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System

Reference 14

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Observation dc46e3eb-cd38-43e4-9c07-f64357f1e901 · outbound

This paper cites Secure federated matrix factorization,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Secure federated matrix factorization,

Reference 15

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source=pdf_text observed=2026-08-05T15:41:00.114598Z digest=sha256:38a19ecb32eaacd1df405fdffe3cd904b84bc781339cb10a7c29d3e07b145663

Observation 3fe1ee54-f41e-42a5-8b40-e7daefcc5b1c · outbound

This paper cites Semi-decentralized federated ego graph learning for recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Semi-decentralized federated ego graph learning for recommendation,

Reference 16

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Observation 114dfbcd-66f6-4030-808a-d5dcd8517a0e · outbound

This paper cites A federated graph neural network framework for privacy-preserving personalization,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions A federated graph neural network framework for privacy-preserving personalization,

Reference 17

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Observation f320c198-21cb-4a34-bbb8-d69e3d817e1c · outbound

This paper cites Fedrec: Federated recommen- dation with explicit feedback,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fedrec: Federated recommen- dation with explicit feedback,

Reference 18

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Observation 5c20cc47-d6c7-40d1-a406-85fc8973e9bd · outbound

This paper cites Fedrec++: Lossless federated recom- mendation with explicit feedback,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fedrec++: Lossless federated recom- mendation with explicit feedback,

Reference 19

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Observation c8eceda2-5233-4889-ae66-3057558bc790 · outbound

This paper cites Stronger privacy for federated collaborative filtering with implicit feedback,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Stronger privacy for federated collaborative filtering with implicit feedback,

Reference 20

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Observation 9e2612c8-4dc9-474d-afe5-2b846f0dedfb · outbound

This paper cites Fr-fmss: Federated recommendation via fake marks and secret sharing,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fr-fmss: Federated recommendation via fake marks and secret sharing,

Reference 21

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Observation c535e28b-e131-46d5-8c6a-5d996788a29e · outbound

This paper cites Federated neural collaborative filtering,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Federated neural collaborative filtering,

Reference 22

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Observation 92d7ae19-be15-4360-8d16-68ec4071f6e7 · outbound

This paper cites Hfsa: A semi-asynchronous hierarchical federated recommendation system in smart city,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Hfsa: A semi-asynchronous hierarchical federated recommendation system in smart city,

Reference 23

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source=pdf_text observed=2026-08-05T15:41:00.153364Z digest=sha256:053e89074c103566bb1a059d737cacadc5aeca17d024d86feff057ca689b1b9b

Observation 0745022e-bf72-4954-bb65-158140cbc5d0 · outbound

This paper cites Marking the pace: A blockchain-enhanced privacy-traceable strategy for federated recom- mender systems,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Marking the pace: A blockchain-enhanced privacy-traceable strategy for federated recom- mender systems,

Reference 24

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source=pdf_text observed=2026-08-05T15:41:00.157886Z digest=sha256:d872e9846a2a2c54e1bf09e400e22394f2fe76fdddb3a26e36c60d0d45b5fbc4

Observation c206b47b-3329-41a6-9910-c14b6fd1abfc · outbound

This paper cites Hn3s: A federated autoencoder framework for collaborative filtering via hybrid negative sampling and secret sharing,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Hn3s: A federated autoencoder framework for collaborative filtering via hybrid negative sampling and secret sharing,

Reference 25

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Observation 951fb2d9-6e0b-48f3-90c4-b6635127ad8a · outbound

This paper cites Federated unlearning for on-device recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Federated unlearning for on-device recommendation,

Reference 26

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Observation 5c95ad66-07ef-4947-b8fe-8aa29eeb0ee4 · outbound

This paper cites Efficient federated item similarity model for privacy-preserving recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Efficient federated item similarity model for privacy-preserving recommendation,

Reference 27

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source=pdf_text observed=2026-08-05T15:41:00.173799Z digest=sha256:7239502aa6699ab5c5e874d563311aadb5c78f91e577d029b115b54cdbf23f48

Observation d5cdfa3b-d332-4018-9ca3-d40f46e1af63 · outbound

This paper cites Fast-adapting and privacy-preserving federated recommender system,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fast-adapting and privacy-preserving federated recommender system,

Reference 28

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Observation 2a471d3c-3fb4-48e6-b7ca-f16098b3afec · outbound

This paper cites Privacy-preserving sequential recommendation with collaborative confusion,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Privacy-preserving sequential recommendation with collaborative confusion,

Reference 29

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Observation 46bae754-ba0f-415a-9d30-b65c5b9802cc · outbound

This paper cites Certified unlearning for federated recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Certified unlearning for federated recommendation,

Reference 30

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Observation 9f71192f-e7a8-4480-9c81-a10acff527d4 · outbound

This paper cites Federated recommender system based on diffusion augmentation and guided denoising,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Federated recommender system based on diffusion augmentation and guided denoising,

Reference 31

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Observation ecef482a-2f2a-41ab-a1b8-80625a9d2958 · outbound

This paper cites Ownership verification for federated recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Ownership verification for federated recommendation,

Reference 32

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source=pdf_text observed=2026-08-05T15:41:00.198926Z digest=sha256:67bf210b42adf07c91a588fcef61fdf0ff6de6d1b760ac418299a93dc6a3a4e0

Observation 0c73af91-24e2-4850-928e-6bb33148de25 · outbound

This paper cites Fedfast: Going beyond average for faster training of federated recommender systems,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fedfast: Going beyond average for faster training of federated recommender systems,

Reference 33

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Observation 50b3299a-b1c3-4e74-9808-115f9e5e8610 · outbound

This paper cites Privacy-preserving news recommendation model learning,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Privacy-preserving news recommendation model learning,

Reference 34

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source=pdf_text observed=2026-08-05T15:41:00.210486Z digest=sha256:9ced56d5622d1dc50599e4c5e7f792f3938cf8f7379cfba1c1180d51f0a0c159

Observation 081b0961-f77e-457b-9bc8-f44150c35488 · outbound

This paper cites Towards fair federated recommendation learning: Characterizing the inter-dependence of system and data heterogeneity,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Towards fair federated recommendation learning: Characterizing the inter-dependence of system and data heterogeneity,

Reference 35

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source=pdf_text observed=2026-08-05T15:41:00.218491Z digest=sha256:cb08050d595bf75c4103d230724c08078cd5ea97bec85a0a98ed7aa9a4129413

Observation 8e036e57-03ca-4fba-a9de-ac0112ad6f4c · outbound

This paper cites Personalized federated recommendation via joint representation learning, user clustering, and model adaptation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Personalized federated recommendation via joint representation learning, user clustering, and model adaptation,

Reference 36

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source=pdf_text observed=2026-08-05T15:41:00.225877Z digest=sha256:f75949c1707d558181d24d1210c94246695cc28bc5085d3b6fe905cd4ecf8c27

Observation 3e2a5f02-840a-45f5-a324-9e70a9b6ec11 · outbound

This paper cites Perfe- drec++: Enhancing personalized federated recommendation with self- supervised pre-training,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Perfe- drec++: Enhancing personalized federated recommendation with self- supervised pre-training,

Reference 37

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source=pdf_text observed=2026-08-05T15:41:00.241744Z digest=sha256:25b0dd5b1990c6d1cb6247d75cbea8940c1600f234b5644bb3c1467ac4a6a029

Observation 54af6dd6-c6da-4629-afa7-95032642071e · outbound

This paper cites Fine-grained preference-aware personalized federated poi recommendation with data sparsity,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fine-grained preference-aware personalized federated poi recommendation with data sparsity,

Reference 38

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Observation a2459e0c-9b51-499c-9daa-41fb407d1fbb · outbound

This paper cites Cluster-driven personalized federated recommendation with interest-aware graph convolution network for multimedia,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Cluster-driven personalized federated recommendation with interest-aware graph convolution network for multimedia,

Reference 39

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Observation 71a15e9d-f7d6-4b0d-8896-7c8b92c53438 · outbound

This paper cites A payload optimization method for federated recommender systems,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions A payload optimization method for federated recommender systems,

Reference 40

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Observation 6e05892a-9503-4eeb-aef0-0f3b1eaa1383 · outbound

This paper cites Towards efficient communication and secure federated recommendation system via low-rank training,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Towards efficient communication and secure federated recommendation system via low-rank training,

Reference 41

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source=pdf_text observed=2026-08-05T15:41:00.265110Z digest=sha256:6812f40bcccd5f5e2ed3ac0e411fc7022a0bf4f729fe3ee41db063234cec373f

Observation 441487c0-f3db-479d-a609-b82c57c23d85 · outbound

This paper cites P4gcn: Vertical federated social recommendation with privacy-preserving two-party graph convolution network,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions P4gcn: Vertical federated social recommendation with privacy-preserving two-party graph convolution network,

Reference 42

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source=pdf_text observed=2026-08-05T15:41:00.270878Z digest=sha256:ef6579ef4b02cbc4411f09f9cb80a2a748ab816891cf227471c4ce62cc861e06

Observation 886247cd-a191-4051-bd1e-93d6877d52d1 · outbound

This paper cites Lightfr: Lightweight fed- erated recommendation with privacy-preserving matrix factorization,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Lightfr: Lightweight fed- erated recommendation with privacy-preserving matrix factorization,

Reference 43

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source=pdf_text observed=2026-08-05T15:41:00.276323Z digest=sha256:6830e86e6e330228be077f43073aa01f7a3cf5e0d55871a378c83ad7296bcd4d

Observation a83429e2-b442-40ca-9b96-f0d89d6fada2 · outbound

This paper cites Discrete federated multi- behavior recommendation for privacy-preserving heterogeneous one- class collaborative filtering,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Discrete federated multi- behavior recommendation for privacy-preserving heterogeneous one- class collaborative filtering,

Reference 44

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source=pdf_text observed=2026-08-05T15:41:00.281497Z digest=sha256:b601ce355f5a9ef9aff4a35f1169517d5f80c9a0378bff3aa74bab24528a82c4

Observation 8b92f8b5-be58-4965-8d37-4634b2621999 · outbound

This paper cites Efficient-fedrec: Efficient federated learning framework for privacy-preserving news recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Efficient-fedrec: Efficient federated learning framework for privacy-preserving news recommendation,

Reference 45

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source=pdf_text observed=2026-08-05T15:41:00.286216Z digest=sha256:f40af500f5a44531acdca107937a51e42803eb951faec74451129630b3ff30e5

Observation cafada0c-f8c0-4495-bd6c-2afb27e7f8a0 · outbound

This paper cites Hide your model: A parameter transmission-free federated recommender system,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Hide your model: A parameter transmission-free federated recommender system,

Reference 46

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source=pdf_text observed=2026-08-05T15:41:00.290712Z digest=sha256:4ddbd7cc02186a6b85bcf70beed21c0d2fee99581ece9aa61c71173da9242de7

Observation 9db5866c-4d67-4351-9745-45c458225ee1 · outbound

This paper cites Personalized federated recommendation for cold-start users via adap- tive knowledge fusion,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Personalized federated recommendation for cold-start users via adap- tive knowledge fusion,

Reference 47

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source=pdf_text observed=2026-08-05T15:41:00.295141Z digest=sha256:5928a35cf94d159fb5cb9a64b36562178874954a43a1dc8b9e5951ccd832d809

Observation 3c52c324-afd1-48b5-8f0e-f56bd196e278 · outbound

This paper cites Privacy- preserving graph convolution network for federated item recommenda- tion,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Privacy- preserving graph convolution network for federated item recommenda- tion,

Reference 48

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source=pdf_text observed=2026-08-05T15:41:00.299838Z digest=sha256:bccfcb02f17f3a062c20453cfc534dc86be0ed602441489ffd627cc5cb76cdf2

Observation 7517c3bc-017f-4384-af8b-2b40741353f4 · outbound

This paper cites Vertical federated graph neural network for recommender system,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Vertical federated graph neural network for recommender system,

Reference 49

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source=pdf_text observed=2026-08-05T15:41:00.305030Z digest=sha256:8a12cd76cacf610a63140f6afa72468f6bf816e89a59caddc87ac721afe29e13

Observation cbf47611-8b70-48d9-9553-ab5ab3c592c6 · outbound

This paper cites Towards personalized privacy: User-governed data contribution for federated recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Towards personalized privacy: User-governed data contribution for federated recommendation,

Reference 50

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source=pdf_text observed=2026-08-05T15:41:00.310423Z digest=sha256:9d2322ca897e18d21fe0e0ce0aa48ca429f608b4eb679b6d2a80d2fb450351ea

Observation 4f8f2560-e21c-4c2f-a86d-d02f7a01931d · outbound

This paper cites Federated heterogeneous graph neural network for privacy-preserving recommen- dation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Federated heterogeneous graph neural network for privacy-preserving recommen- dation,

Reference 51

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source=pdf_text observed=2026-08-05T15:41:00.315358Z digest=sha256:fa6363b5d99c3a482976b394b202f28812f91c2e482cdfb5286089d7cbe9af6f

Observation 3cef03a8-95f7-4d28-bbd8-0007133d60a2 · outbound

This paper cites Defedgcn: Privacy-preserving decentralized federated gcn for recommender sys- tem,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Defedgcn: Privacy-preserving decentralized federated gcn for recommender sys- tem,

Reference 52

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source=pdf_text observed=2026-08-05T15:41:00.320267Z digest=sha256:9416e0fa6d74183087498ce2ad95de065fdef52f4fdf51b0c77b89f77cb67237

Observation b7a7e24b-c98f-4117-8568-296ca7401faa · outbound

This paper cites Poisoning deep learning based recom- mender model in federated learning scenarios,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Poisoning deep learning based recom- mender model in federated learning scenarios,

Reference 53

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source=pdf_text observed=2026-08-05T15:41:00.325685Z digest=sha256:698ba70cbe901294a0b483d3d6b8d0132456bcf4f7f30776fa520a3cb960dc67

Observation 997261e5-ac66-4e48-b263-cdb308ad46c6 · outbound

This paper cites Fedattack: Effective and covert poisoning attack on federated recommendation via hard sampling,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fedattack: Effective and covert poisoning attack on federated recommendation via hard sampling,

Reference 55

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Observation c95f728b-90ac-4d7f-b159-55349793e569 · outbound

This paper cites Pipattack: Poisoning federated recommender systems for manipulating item promotion,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Pipattack: Poisoning federated recommender systems for manipulating item promotion,

Reference 56

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source=pdf_text observed=2026-08-05T15:41:00.341869Z digest=sha256:1d1d3c4e8df4b49baeaf8cddb518f8ec0c2139fc255b94f151953f3c26cc91a1

Observation 4ce9afb1-7649-42fb-9a21-7ebb740dec2e · outbound

This paper cites Ua-fedrec: untargeted attack on federated news recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Ua-fedrec: untargeted attack on federated news recommendation,

Reference 57

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source=pdf_text observed=2026-08-05T15:41:00.346808Z digest=sha256:43ec5104eabd5200cf6a29592ab7aafbb5fa9750a56c11d5356b417d986c23c7

Observation 48963c63-2dd5-4c30-9570-a56fe1a99532 · outbound

This paper cites Untargeted attack against federated recommendation systems via poisonous item embeddings and the defense,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Untargeted attack against federated recommendation systems via poisonous item embeddings and the defense,

Reference 58

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source=pdf_text observed=2026-08-05T15:41:00.352720Z digest=sha256:bf8ae993fc7dcec78f49687d6751499c9c64c6678d154830d6b26c2ce2733269

Observation aa63bf40-5c36-4c5e-bfe4-df7692293b0a · outbound

This paper cites Interaction-level membership inference attack against federated rec- ommender systems,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Interaction-level membership inference attack against federated rec- ommender systems,

Reference 59

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Observation 937f3216-0e03-4a6c-9602-c13d5476d638 · outbound

This paper cites Comprehensive privacy analysis on federated recommender system against attribute inference attacks,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Comprehensive privacy analysis on federated recommender system against attribute inference attacks,

Reference 60

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source=pdf_text observed=2026-08-05T15:41:00.362720Z digest=sha256:4d050cb3d0840049374d11b8d5251bbc33a5bc7f3281fe437b9fe463b5d07802

Observation 7d34c098-4656-4d9c-a73a-7d462c1e1ed3 · outbound

This paper cites Not one less: Exploring interplay between user profiles and items in untargeted attacks against federated recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Not one less: Exploring interplay between user profiles and items in untargeted attacks against federated recommendation,

Reference 61

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source=pdf_text observed=2026-08-05T15:41:00.368621Z digest=sha256:cefdc02d9447c2a338ede1fdc0be9941ee8a37b0298da08dc8c73cfc8fd322bc

Observation f95280a0-5207-45e7-872f-5f9b575eb1a8 · outbound

This paper cites Eyes on federated recommendation: Targeted poisoning with compe- tition and its mitigation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Eyes on federated recommendation: Targeted poisoning with compe- tition and its mitigation,

Reference 62

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source=pdf_text observed=2026-08-05T15:41:00.373381Z digest=sha256:885864b85c1687e6d3f19f4b5096958a0df197e200902e734f311c63e9edf599

Observation c16df262-777f-429b-8ee6-a03c8501bfd5 · outbound

This paper cites User consented federated recommender system against personalized attribute inference attack,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions User consented federated recommender system against personalized attribute inference attack,

Reference 63

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source=pdf_text observed=2026-08-05T15:41:00.377979Z digest=sha256:f1831816bd7bed8d6b47acf35847221bbb2cb058b1d26a7236ce51608ad606cd

Observation 5a535ee0-b125-452c-a575-a417ac0c0669 · outbound

This paper cites Defending against membership inference attack for counterfactual federated recommendation with differentially private representation learning,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Defending against membership inference attack for counterfactual federated recommendation with differentially private representation learning,

Reference 64

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source=pdf_text observed=2026-08-05T15:41:00.382605Z digest=sha256:7eefff3231a83b1901e92465a665bf5cbafcffda95c2f8791d4c02cad63ad924

Observation f8181eb5-e5d2-4afa-bfe0-eaab31b1a002 · outbound

This paper cites Poisoning federated recommender systems with fake users,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Poisoning federated recommender systems with fake users,

Reference 65

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Observation 47450f0f-3fdf-48fa-aef9-11efbb9b0067 · outbound

This paper cites Preventing the popular item embedding based attack in federated recommenda- tions,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Preventing the popular item embedding based attack in federated recommenda- tions,

Reference 66

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source=pdf_text observed=2026-08-05T15:41:00.393548Z digest=sha256:68aa6a6fd377855a611e52b5e129e1776065036564a5014e17529ecc94fa083c

Observation cb22893c-43c8-452b-85b4-25a23c014d2c · outbound

This paper cites Poisoning decentralized collaborative recommender system and its countermea- sures,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Poisoning decentralized collaborative recommender system and its countermea- sures,

Reference 67

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Observation 1ac0621b-1fca-441a-8b49-3f7bab578f6a · outbound

This paper cites Hidattack: An effective and undetectable model poisoning attack to federated recommenders,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Hidattack: An effective and undetectable model poisoning attack to federated recommenders,

Reference 68

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source=pdf_text observed=2026-08-05T15:41:00.403302Z digest=sha256:bbe14b0a103da7be47f6aebfa08bbc49d19dd5ea708d2cbc5853f1a39a4018a6

Observation 2323263c-b841-4b89-ba9a-608c986fc941 · outbound

This paper cites Defending federated recommender systems against untargeted attacks: A contribution-aware robust aggregation scheme,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Defending federated recommender systems against untargeted attacks: A contribution-aware robust aggregation scheme,

Reference 69

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Observation 39974c5c-b211-4f53-82d2-3bbb4d451224 · outbound

This paper cites Aegis: Post-training attribute unlearning in federated recommender systems against attribute inference attacks,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Aegis: Post-training attribute unlearning in federated recommender systems against attribute inference attacks,

Reference 70

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source=pdf_text observed=2026-08-05T15:41:00.417974Z digest=sha256:5fddc2c0183a4584dddbcd6b4d5ffd28bfd129b548fda4a43745b0385a925a3f

Observation 40f72f1b-29f6-4b90-8257-c5896bdb9b01 · outbound

This paper cites Fedcdr: federated cross-domain recommendation for privacy- preserving rating prediction,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fedcdr: federated cross-domain recommendation for privacy- preserving rating prediction,

Reference 72

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source=pdf_text observed=2026-08-05T15:41:00.434531Z digest=sha256:23a2dc3f513a5551000bef7c86eeb4d911149293f50d6cfea16aeaa6ba69f18b

Observation 37b1efa8-e422-4633-93fb-a7c7e9329d4c · outbound

This paper cites Fedcore: Federated learning for cross-organization recommendation ecosystem,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fedcore: Federated learning for cross-organization recommendation ecosystem,

Reference 73

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Observation b568a58c-a69d-45a0-854d-03c315eae3bd · outbound

This paper cites Ppgencdr: A stable and robust framework for privacy-preserving cross-domain recommen- dation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Ppgencdr: A stable and robust framework for privacy-preserving cross-domain recommen- dation,

Reference 74

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source=pdf_text observed=2026-08-05T15:41:00.446055Z digest=sha256:25c502dc672728cac32a9c9b5d4ef9e5875675c0ed239f745bb78a40884f8d65

Observation 41ccda01-3fb2-4083-97e2-79b26a737b0b · outbound

This paper cites Federated graph learning for cross-domain recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Federated graph learning for cross-domain recommendation,

Reference 75

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Observation 0eb9312a-b55a-4e76-bf81-ec65d91c36af · outbound

This paper cites Privacy-preserving cross-domain se- quential recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Privacy-preserving cross-domain se- quential recommendation,

Reference 76

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source=pdf_text observed=2026-08-05T15:41:00.455887Z digest=sha256:61f3c26703eff5ea4d6f62a29a77e6adbea47c4e19a666b06ed54c11f35e2984

Observation 50954348-5485-48fe-88ae-5e48a49f9c94 · outbound

This paper cites Fedct: Federated collaborative transfer for recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fedct: Federated collaborative transfer for recommendation,

Reference 77

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source=pdf_text observed=2026-08-05T15:41:00.460782Z digest=sha256:7b9a52f77ffdc54053bd9604aec864681aab4843a219f21a402412e4d5fea971

Observation efb8d453-2768-4bb4-9c11-e028a67685de · outbound

This paper cites Feder- ated probabilistic preference distribution modelling with compactness co-clustering for privacy-preserving multi-domain recommendation.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Feder- ated probabilistic preference distribution modelling with compactness co-clustering for privacy-preserving multi-domain recommendation

Reference 78

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source=pdf_text observed=2026-08-05T15:41:00.466311Z digest=sha256:015151d1ba5e4bbd5f72a4ccc5b21df93ab3b211420e4783121a02f609efdfe1

Observation 360cfc5f-1a91-4cf7-935d-34c14255aac0 · outbound

This paper cites Differential private knowledge transfer for privacy-preserving cross-domain recom- mendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Differential private knowledge transfer for privacy-preserving cross-domain recom- mendation,

Reference 79

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source=pdf_text observed=2026-08-05T15:41:00.471800Z digest=sha256:957a1511655d584f6303814ae8d2254e6660585ecf30f5cf42b1fa7b7a84ca72

Observation 0ca5693c-1a23-48b0-9053-647acbcee97c · outbound

This paper cites Differentially private sparse mapping for privacy-preserving cross domain recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Differentially private sparse mapping for privacy-preserving cross domain recommendation,

Reference 80

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source=pdf_text observed=2026-08-05T15:41:00.476737Z digest=sha256:895a85b5d4e6c77674509286f9c0445dae3c41de8cc31a67fce0504d8fcd5c27

Observation 67db3f12-cf4a-47ec-8605-49dc8560cb85 · outbound

This paper cites A federated multi-view deep learning framework for privacy-preserving recommendations,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions A federated multi-view deep learning framework for privacy-preserving recommendations,

Reference 81

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source=pdf_text observed=2026-08-05T15:41:00.481971Z digest=sha256:1c4b8046000e248bf75a80f793243496606428779ac656cf16d3352e864c047c

Observation 3d6c2055-6669-496d-ac26-8e5ed270bfed · outbound

This paper cites Refer: Retrieval-enhanced vertical federated recommendation for full set user benefit,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Refer: Retrieval-enhanced vertical federated recommendation for full set user benefit,

Reference 82

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source=pdf_text observed=2026-08-05T15:41:00.487612Z digest=sha256:ccd3cadb3f20997daffcbcd47ca361f307a9b011aa7883c05f3306dc1afd8ffa

Observation b85ea1e7-7852-438f-865d-81ed57b3b39e · outbound

This paper cites Feddcsr: Federated cross-domain sequential recommendation via disentangled representation learning,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Feddcsr: Federated cross-domain sequential recommendation via disentangled representation learning,

Reference 83

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source=pdf_text observed=2026-08-05T15:41:00.493129Z digest=sha256:e3c6e70d7de7c93f91dbd2ab38a26e640cc165f7231e5f10cf5e41e9627fb3d8

Observation 64701344-c629-4d83-8751-0925913f70c2 · outbound

This paper cites Fedhcdr: Federated cross-domain recommendation with hypergraph signal decoupling,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fedhcdr: Federated cross-domain recommendation with hypergraph signal decoupling,

Reference 84

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source=pdf_text observed=2026-08-05T15:41:00.498240Z digest=sha256:9cbcc18130c3a9d57d5252f59cfbaef518e14a5cc25b83204d13f41d11849651

Observation 618432b7-78f4-4206-82e7-dd376bc0850d · outbound

This paper cites Win-win: a privacy-preserving federated framework for dual-target cross-domain recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Win-win: a privacy-preserving federated framework for dual-target cross-domain recommendation,

Reference 85

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source=pdf_text observed=2026-08-05T15:41:00.502861Z digest=sha256:aefd15e9b7a01284c5a297d3d18cb04be1ceb0d7633041ea41f200d731ea7f4a

Observation 94f3fbb1-8176-4c06-ad99-1125061c20a4 · outbound

This paper cites Fedcsr: A federated framework for multi-platform cross-domain sequential recommendation with dual contrastive learning,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fedcsr: A federated framework for multi-platform cross-domain sequential recommendation with dual contrastive learning,

Reference 86

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source=pdf_text observed=2026-08-05T15:41:00.508160Z digest=sha256:9c6422ad90659bdacf85ed9296bec69dfe0bbaea8d1dffdb8e2802f91b2039e4

Observation 1328cf90-9ec7-43aa-8948-c75c697ed1c6 · outbound

This paper cites Privacy-preserving cross-domain recommendation with federated graph learning,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Privacy-preserving cross-domain recommendation with federated graph learning,

Reference 87

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source=pdf_text observed=2026-08-05T15:41:00.513702Z digest=sha256:1c4c77f6aa3e30f98c0f89bf7fbc8480e0745405b3fe5ca4936a0c841170e57c

Observation ba5e5cd0-1fad-49f6-bb6b-e5d11b51e816 · outbound

This paper cites Prompt- enhanced federated content representation learning for cross-domain recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Prompt- enhanced federated content representation learning for cross-domain recommendation,

Reference 88

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source=pdf_text observed=2026-08-05T15:41:00.518335Z digest=sha256:6d9723224c4044fde4342a6206b812ad3a176fe90acf6cc87b969d92bd9d2d16

Observation 6dff6a5c-98bf-46e5-9af1-c0f654d4f7c0 · outbound

This paper cites Recommendation algorithm based on federated multi-modal learning,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Recommendation algorithm based on federated multi-modal learning,

Reference 89

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source=pdf_text observed=2026-08-05T15:41:00.523316Z digest=sha256:068d694d1d9aca8c276a7299e73a66ea118e513e66ee157626076ba7b8a36dc4

Observation 253570d7-7e37-4894-8d09-dc33e2c4f8df · outbound

This paper cites Towards resource-efficient and secure federated multimedia recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Towards resource-efficient and secure federated multimedia recommendation,

Reference 90

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source=pdf_text observed=2026-08-05T15:41:00.529199Z digest=sha256:11a0a1c849016e1e36eb3101eca2e8718da6e2526f4ed013729d476e8095fe3d

Observation e952882c-17ef-435b-9b27-6657e839b110 · outbound

This paper cites A privacy-preserving framework with multi-modal data for cross-domain recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions A privacy-preserving framework with multi-modal data for cross-domain recommendation,

Reference 91

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source=pdf_text observed=2026-08-05T15:41:00.535481Z digest=sha256:d66b1f8efcea7cb3b5c98f672c0db7af42442dff9271f628cff4cd96c6966bd7

Observation a94b8c92-e3ee-40dc-8715-99e1d8974dcc · outbound

This paper cites Personalized item em- beddings in federated multimodal recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Personalized item em- beddings in federated multimodal recommendation,

Reference 92

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source=pdf_text observed=2026-08-05T15:41:00.540534Z digest=sha256:56d95f4914755950dc1c14d852e5f59d692a6e799306481cb80591506125e862

Observation 62949ca1-7c2f-44b5-bd53-3539b6156bbf · outbound

This paper cites Federated adaptation for foundation model-based recommendations,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Federated adaptation for foundation model-based recommendations,

Reference 93

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source=pdf_text observed=2026-08-05T15:41:00.545539Z digest=sha256:53c850e2d802ff0d25897a87ea60d469a93503333d3f135d156db066e17c40b6

Observation a9fc3852-f0df-49bf-8cc1-91b5aba7b898 · outbound

This paper cites A Federated Framework for LLM-based Recommendation.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions A Federated Framework for LLM-based Recommendation

Reference 94

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source=pdf_text observed=2026-08-05T15:41:00.550584Z digest=sha256:e535754e0354bfdcd22ee49e0c42b0c938a89500ad41411dc95fa6e32f2c6379

Observation 28680a13-a66b-4f08-8cef-56c29efe8e98 · outbound

This paper cites Fellas: Enhancing federated sequential recommendation with llm as external services,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fellas: Enhancing federated sequential recommendation with llm as external services,

Reference 95

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source=pdf_text observed=2026-08-05T15:41:00.555729Z digest=sha256:f92bc02c6dfd504cae92a6539826b125dba4fd2796d61ae9480d452e7da1ff63

Observation 6ac7772e-1554-4955-a2e2-600e9f991922 · outbound

This paper cites Multifaceted user modeling in recommendation: A federated foundation models approach,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Multifaceted user modeling in recommendation: A federated foundation models approach,

Reference 96

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source=pdf_text observed=2026-08-05T15:41:00.561802Z digest=sha256:cfd6b77ec2cf92921dbf2698098b711334d695a31c788320ef0cd979bcca5f47

Observation 3ad51145-27fe-4e14-922e-beb38564c448 · outbound

This paper cites Federated rec- ommendation systems,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Federated rec- ommendation systems,

Reference 97

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source=pdf_text observed=2026-08-05T15:41:00.567959Z digest=sha256:3d98674b67a3455552549c0febb06faa912f01dfd156968a0e1c78b46e506f17

Observation 87739092-3bd9-4d95-9fce-d5249550f067 · outbound

This paper cites Horizontal federated recommender system: A survey,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Horizontal federated recommender system: A survey,

Reference 98

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source=pdf_text observed=2026-08-05T15:41:00.574044Z digest=sha256:ee4ed584910b851ebac7085560cad9d430b6bf0f900e0a6a6253e40008323e5b

Observation 0d28ab7c-cf83-4ab4-9b5d-5f4381115dcb · outbound

This paper cites Navigating the Future of Federated Recommendation Systems with Foundation Models.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Navigating the Future of Federated Recommendation Systems with Foundation Models

Reference 99

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source=pdf_text observed=2026-08-05T15:41:00.579311Z digest=sha256:7e61c50b2d680de401a1866482a63d6a8dbb19dddf014e4a2f024c04ac960ccb

Observation 9d97b12f-1a01-4613-9426-fd5295943323 · outbound

This paper cites A survey on cross-user federated recommendation,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions A survey on cross-user federated recommendation,

Reference 100

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source=pdf_text observed=2026-08-05T15:41:00.585604Z digest=sha256:84af225990d7a76ef12a7182e991171dd7a450cd79ecbe340b791eaa24a2c16f

Observation 7581b777-02b9-44dd-8f29-e47b3c07d547 · outbound

This paper cites Fast matrix factorization for online recommendation with implicit feedback,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Fast matrix factorization for online recommendation with implicit feedback,

Reference 101

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source=pdf_text observed=2026-08-05T15:41:00.592069Z digest=sha256:4e2fb531f4bcbce8217a26293ada25ec1ca589ed02d78af1488a9ad48ee9ebd5

Observation 6e6cd8df-9a37-4c2c-b845-e319a974afa9 · outbound

This paper cites Explicit factor models for explainable recommendation based on phrase-level sentiment analysis,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Explicit factor models for explainable recommendation based on phrase-level sentiment analysis,

Reference 102

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source=pdf_text observed=2026-08-05T15:41:00.598158Z digest=sha256:015c930d7ca2f5b5d2c1b23e2cdbe98075c7725b8a7d50b334d819be9abf2444

Observation f421c6e4-c7df-431d-99dc-bcdfaf3d6cb9 · outbound

This paper cites Communication-efficient learning of deep networks from decentral- ized data,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Communication-efficient learning of deep networks from decentral- ized data,

Reference 103

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source=pdf_text observed=2026-08-05T15:41:00.603967Z digest=sha256:8c54687bf51445659ade814d9e000b80900ad808af1df9d89770ff5f8d1024c9

Observation 15a238d7-e693-4171-8129-3b8c31dac284 · outbound

This paper cites Bpr: Bayesian personalized ranking from implicit feedback,.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions Bpr: Bayesian personalized ranking from implicit feedback,

Reference 104

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Pith citing papers

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