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Paper Citation Record · LEDGER

A Survey on Sequential Recommendation

As of 13 August 2026, this Paper Citation Record lists 100 of 199 outbound references and 3 inbound Pith citation observations for arXiv:2412.12770.

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

pith.paper-citation-record.v1
2412.12770 v2

Coverage vector

measured 100 of 199 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:47:37.563307Z

measured 103 of 103 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:16:33.881146Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

100 of 199 outbound references displayed

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  • verified fuzzy0
  • unresolved99
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  • malformed identifier0
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External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 726cd4d8-b441-4751-bf96-831aed34817f · outbound

This paper cites Self-attentive sequential rec- ommendation.

A Survey on Sequential Recommendation Self-attentive sequential rec- ommendation

Reference 1

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Observation f5d24116-030a-4d2f-809e-ffcb1ebf4fc2 · outbound

This paper cites Translation-based rec- ommendation.

A Survey on Sequential Recommendation Translation-based rec- ommendation

Reference 2

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Observation de2f447f-f1c2-4272-b3b6-bac68069bdec · outbound

This paper cites ICAT-SR: Item categorical attribute integrated sequential recom- mendation.

A Survey on Sequential Recommendation ICAT-SR: Item categorical attribute integrated sequential recom- mendation

Reference 3

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Observation e9c42940-6663-490f-8e50-45aa734b4414 · outbound

This paper cites Non- invasive self-attention for side information fusion in sequential recommendation.

A Survey on Sequential Recommendation Non- invasive self-attention for side information fusion in sequential recommendation

Reference 4

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Observation d76e15f7-feba-4a17-a55c-1d7e2c2ceff2 · outbound

This paper cites BERT: Pre- training of deep bidirectional Transformers for lan- guage understanding.

A Survey on Sequential Recommendation BERT: Pre- training of deep bidirectional Transformers for lan- guage understanding

Reference 5

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Observation 154a49a4-f4ab-4bb9-8f75-6ced2dd3b8bd · outbound

This paper cites Deep residual learning for image recognition.

A Survey on Sequential Recommendation Deep residual learning for image recognition

Reference 6

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Observation 42ffd1b7-c208-447c-9df2-e714a7f9bfcc · outbound

This paper cites Where to go next for recommender systems? ID- vs.

A Survey on Sequential Recommendation Where to go next for recommender systems? ID- vs

Reference 7

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Observation 6fe0dd79-ebc6-4c09-8bc0-4b3eea648c5e · outbound

This paper cites Towards universal sequence representation learning for recommender systems.

A Survey on Sequential Recommendation Towards universal sequence representation learning for recommender systems

Reference 8

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Observation 602e1e4a-c25d-4669-91c2-a34987224e51 · outbound

This paper cites GenRec: Large language model for generative recommendation.

A Survey on Sequential Recommendation GenRec: Large language model for generative recommendation

Reference 9

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Observation dc4d3fae-1226-4f57-8e02-9cab96635f38 · outbound

This paper cites Improving sequential rec- ommendations with LLMs.

A Survey on Sequential Recommendation Improving sequential rec- ommendations with LLMs

Reference 10

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Observation eabbdc99-d727-4fbd-a803-ae6b4addb3ea · outbound

This paper cites Search-based user interest modeling with lifelong sequential behavior data for click-through rate prediction.

A Survey on Sequential Recommendation Search-based user interest modeling with lifelong sequential behavior data for click-through rate prediction

Reference 11

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Observation 917f286e-2393-443a-9b48-74375ed3000a · outbound

This paper cites Contrastive learning for sequential recommendation.

A Survey on Sequential Recommendation Contrastive learning for sequential recommendation

Reference 12

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Observation 22976b54-bf22-47ba-bff3-64eb19f9022a · outbound

This paper cites A survey on session-based recommender systems.

A Survey on Sequential Recommendation A survey on session-based recommender systems

Reference 13

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Observation 8e7164ce-5c2a-4f52-a9da-ce4bfdb53622 · outbound

This paper cites Graph and sequential neural networks in session-based recommendation: A survey.

A Survey on Sequential Recommendation Graph and sequential neural networks in session-based recommendation: A survey

Reference 14

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Observation 893e47f1-8679-4fe7-965c-e37c89462a73 · outbound

This paper cites Sequence-aware recommender systems.

A Survey on Sequential Recommendation Sequence-aware recommender systems

Reference 15

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Observation fc4d3491-76e7-43aa-870a-e6a951ef61bb · outbound

This paper cites A survey and taxonomy of se- quential recommender systems for e-commerce prod- uct recommendation.

A Survey on Sequential Recommendation A survey and taxonomy of se- quential recommender systems for e-commerce prod- uct recommendation

Reference 16

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Observation 4d3f3722-fb0b-46f6-bf32-4bb576a2d64a · outbound

This paper cites Deep learning for sequential recommendation: Algorithms, influential factors, and evaluations.

A Survey on Sequential Recommendation Deep learning for sequential recommendation: Algorithms, influential factors, and evaluations

Reference 17

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Observation 9af58343-96a6-4786-a19f-6e6d4c411151 · outbound

This paper cites A survey of sequential recommendation systems: Techniques, evaluation, and future directions.

A Survey on Sequential Recommendation A survey of sequential recommendation systems: Techniques, evaluation, and future directions

Reference 18

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Observation 2f348e4d-5b4e-4222-978b-1ced57ec32e4 · outbound

This paper cites A survey on multi- behavior sequential recommendation.

A Survey on Sequential Recommendation A survey on multi- behavior sequential recommendation

Reference 19

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Source-reported events for the cited work

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Observation 6069dc24-a430-4389-bb21-4353371a9acb · outbound

This paper cites A survey on cross-domain sequential recommendation.

A Survey on Sequential Recommendation A survey on cross-domain sequential recommendation

Reference 20

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Observation d2d77f1c-1f34-405a-a153-21df58be4043 · outbound

This paper cites Contrastive self- supervised learning in recommender systems: A sur- vey.

A Survey on Sequential Recommendation Contrastive self- supervised learning in recommender systems: A sur- vey

Reference 21

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Observation 4c201df1-51e3-44c6-b847-f8882168a176 · outbound

This paper cites A Survey on Data-Centric Recommender Systems.

A Survey on Sequential Recommendation A Survey on Data-Centric Recommender Systems

Reference 22

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Observation 7b880fb1-b5b5-45c8-be00-dc37d8d6b7c9 · outbound

This paper cites Side Information-Driven Session-based Recommendation: A Survey.

A Survey on Sequential Recommendation Side Information-Driven Session-based Recommendation: A Survey

Reference 23

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Observation 8416464d-14c2-407a-89da-ee7c850aefd0 · outbound

This paper cites Session- based recommendations with recurrent neural networks.

A Survey on Sequential Recommendation Session- based recommendations with recurrent neural networks

Reference 24

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Observation c3e8266c-a87d-478a-b213-9b656b5e5919 · outbound

This paper cites Decoupled side information fusion for sequential recommendation.

A Survey on Sequential Recommendation Decoupled side information fusion for sequential recommendation

Reference 25

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Observation 17ab5a26-30fb-4126-9fa2-e80ff6ca2627 · outbound

This paper cites Extracting attentive social temporal excitation for sequential recommendation.

A Survey on Sequential Recommendation Extracting attentive social temporal excitation for sequential recommendation

Reference 26

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Observation 33346670-7315-46f1-991d-44b7547eaeb7 · outbound

This paper cites Learning vector- 40 Front.

A Survey on Sequential Recommendation Learning vector- 40 Front

Reference 27

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Observation d3247754-757f-4e99-b61b-3b75210b2e9d · outbound

This paper cites Using se- quential and non-sequential patterns in predictive web usage mining tasks.

A Survey on Sequential Recommendation Using se- quential and non-sequential patterns in predictive web usage mining tasks

Reference 28

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Observation b8040470-cb4b-4789-a8e5-a9c0bfe4d28f · outbound

This paper cites Fac- torizing personalized Markov chains for next-basket recommendation.

A Survey on Sequential Recommendation Fac- torizing personalized Markov chains for next-basket recommendation

Reference 29

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Observation aa17ae34-1df1-4d48-bb73-96765fa30659 · outbound

This paper cites Recurrent neural networks with top-k gains for session-based recommendations.

A Survey on Sequential Recommendation Recurrent neural networks with top-k gains for session-based recommendations

Reference 30

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Observation f1ca7f9b-501c-44a6-90e9-90d7b479b51b · outbound

This paper cites K-plet recurrent neural networks for sequential recommendation.

A Survey on Sequential Recommendation K-plet recurrent neural networks for sequential recommendation

Reference 31

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Observation f6096130-69d9-4daa-b485-38e7c0398c20 · outbound

This paper cites Collaborative sequence prediction for sequential recommender.

A Survey on Sequential Recommendation Collaborative sequence prediction for sequential recommender

Reference 32

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Observation dad492bf-6b69-4b5e-9db5-04fa0027b79a · outbound

This paper cites Double attention convolutional neural network for sequential recommen- dation.

A Survey on Sequential Recommendation Double attention convolutional neural network for sequential recommen- dation

Reference 33

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Observation 172a91b4-ac75-4a62-9f83-7d5a278548da · outbound

This paper cites Personalized top-N sequential recom- mendation via convolutional sequence embedding.

A Survey on Sequential Recommendation Personalized top-N sequential recom- mendation via convolutional sequence embedding

Reference 34

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Observation 40a1140f-5ede-4598-b1f6-fd4374e77c76 · outbound

This paper cites Cos- Rec: 2D convolutional neural networks for sequential recommendation.

A Survey on Sequential Recommendation Cos- Rec: 2D convolutional neural networks for sequential recommendation

Reference 35

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Observation dc9af56a-1be2-4acb-aff9-c24b3830db86 · outbound

This paper cites BERT4Rec: Sequential recommendation with bidirec- tional encoder representations from Transformer.

A Survey on Sequential Recommendation BERT4Rec: Sequential recommendation with bidirec- tional encoder representations from Transformer

Reference 36

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Observation 742a15a7-cb35-4164-a01c-6b85c78c935c · outbound

This paper cites A systematic review and repli- cability study of bert4rec for sequential recommenda- tion.

A Survey on Sequential Recommendation A systematic review and repli- cability study of bert4rec for sequential recommenda- tion

Reference 37

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Observation deb5760a-d4e8-40b2-b6b6-313a8809b321 · outbound

This paper cites Adaptive disen- tangled Transformer for sequential recommendation.

A Survey on Sequential Recommendation Adaptive disen- tangled Transformer for sequential recommendation

Reference 38

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Observation 5b913475-af5d-4e82-8911-1b9aaa451f55 · outbound

This paper cites Attention calibration for Transformer-based sequential recommendation.

A Survey on Sequential Recommendation Attention calibration for Transformer-based sequential recommendation

Reference 39

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Observation 31feae7e-6b72-4d0f-a9dd-2c034b8aa2d1 · outbound

This paper cites Sequential recommendation for optimiz- ing both immediate feedback and long-term retention.

A Survey on Sequential Recommendation Sequential recommendation for optimiz- ing both immediate feedback and long-term retention

Reference 40

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Observation 20a2bc0f-5c8c-419a-ac95-c173e8c22084 · outbound

This paper cites Sequential recommendation via stochastic self-attention.

A Survey on Sequential Recommendation Sequential recommendation via stochastic self-attention

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source=pdf_text observed=2026-08-11T13:47:37.274106Z digest=sha256:098c68b39c1f0f0f601b85f174bc6eda965fe8fb1dbedc8e94c7634c689bf2c5

Observation 043e5209-bad4-449e-ad47-479d53845601 · outbound

This paper cites Sequential recommendation with self-attentive multi-adversarial network.

A Survey on Sequential Recommendation Sequential recommendation with self-attentive multi-adversarial network

Reference 42

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source=pdf_text observed=2026-08-11T13:47:37.279380Z digest=sha256:36d8c64d6732c01f10538d5bfa8c329fe2c9962686b5066c192b746598431e83

Observation 8dd98f3c-39c2-4874-bcee-27647ae07171 · outbound

This paper cites SSE-PT: Sequen- tial recommendation via personalized Transformer.

A Survey on Sequential Recommendation SSE-PT: Sequen- tial recommendation via personalized Transformer

Reference 43

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source=pdf_text observed=2026-08-11T13:47:37.284241Z digest=sha256:14b50adae2822b4b9f73643c5d959a84f6ed333dc65d986927fac4a668c465a6

Observation b8a6e4fc-c9ee-4641-9c85-7733eae6b8bf · outbound

This paper cites STRec: Sparse Transformer for sequential recommendations.

A Survey on Sequential Recommendation STRec: Sparse Transformer for sequential recommendations

Reference 44

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source=pdf_text observed=2026-08-11T13:47:37.288927Z digest=sha256:5e88de772249ebea5c561bbc8c1891aabef75021b4bbb8a7270c1acfcd4cd0f8

Observation b2c4dca0-6bce-465b-aaf1-c60c623e21c7 · outbound

This paper cites Motif-aware se- quential recommendation.

A Survey on Sequential Recommendation Motif-aware se- quential recommendation

Reference 45

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source=pdf_text observed=2026-08-11T13:47:37.293265Z digest=sha256:92cf82907ede8c4dfce168405080dd06aee73eeeed6c2fcf0c79e636b6a586af

Observation 379e12e3-e25d-4a88-afb5-85ec361d7446 · outbound

This paper cites Poincar ´e heterogeneous graph neural networks for sequential recommendation.

A Survey on Sequential Recommendation Poincar ´e heterogeneous graph neural networks for sequential recommendation

Reference 46

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source=pdf_text observed=2026-08-11T13:47:37.297929Z digest=sha256:b82bf3c8c86f5b63c46e3459f0549f04fbee1652ebbf9a3380af7243dc27d374

Observation feda4e89-28c0-4f33-8803-b2c9578069a4 · outbound

This paper cites Contrastive learning with bidirectional Transformers for sequential recommendation.

A Survey on Sequential Recommendation Contrastive learning with bidirectional Transformers for sequential recommendation

Reference 47

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source=pdf_text observed=2026-08-11T13:47:37.302910Z digest=sha256:ac87e76e7665afd8944b61315e9d6d2bd9c8cfe0ee3b13f0c2baa895be11729e

Observation ad8cddd2-af2c-4844-bea3-f250472d1f3a · outbound

This paper cites De- biased contrastive learning for sequential recommen- dation.

A Survey on Sequential Recommendation De- biased contrastive learning for sequential recommen- dation

Reference 48

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source=pdf_text observed=2026-08-11T13:47:37.307938Z digest=sha256:5c0b9610a5817deaa3187ff3bc1271443f28e0201505b449bf95813f55b78eaf

Observation c2a6dd26-e4cc-4c23-9d56-b8268c615780 · outbound

This paper cites 41 Jin D, Li Y.

A Survey on Sequential Recommendation 41 Jin D, Li Y

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source=pdf_text observed=2026-08-11T13:47:37.312715Z digest=sha256:f3c8e23ffe062c9e09ab0c43b4a37384398c97482980501e399e3fe043e397e5

Observation c3104c18-657d-4c67-a0b7-e8aaa0b57c50 · outbound

This paper cites Dually en- hanced propensity score estimation in sequential rec- ommendation.

A Survey on Sequential Recommendation Dually en- hanced propensity score estimation in sequential rec- ommendation

Reference 50

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source=pdf_text observed=2026-08-11T13:47:37.317927Z digest=sha256:8fa10ae36d972388a21f14755650d0caba958131722c51e4fca4b82ec023e299

Observation 1acd05f4-5469-4bf0-abaa-d618e0cfdb18 · outbound

This paper cites Improving Transformer-based sequential recom- menders through preference editing.

A Survey on Sequential Recommendation Improving Transformer-based sequential recom- menders through preference editing

Reference 51

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source=pdf_text observed=2026-08-11T13:47:37.322589Z digest=sha256:56f1166b58cad8c2337373eb1bf683d988b4644315c93bbee2f93e5a25511ce8

Observation 2237cb2c-86ab-443f-ada5-98b50dfcaf69 · outbound

This paper cites Integrating offline reinforcement learning with Transformers for se- quential recommendation.

A Survey on Sequential Recommendation Integrating offline reinforcement learning with Transformers for se- quential recommendation

Reference 52

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source=pdf_text observed=2026-08-11T13:47:37.327653Z digest=sha256:ca3daf15d4408e71581708a99924cccc2ed19b8ca6b594094bcb3b6635977ebc

Observation a3477d96-61f7-4f26-bef6-9bf2b74650fa · outbound

This paper cites Modeling se- quences as distributions with uncertainty for sequential recommendation.

A Survey on Sequential Recommendation Modeling se- quences as distributions with uncertainty for sequential recommendation

Reference 53

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source=pdf_text observed=2026-08-11T13:47:37.332338Z digest=sha256:116bf721cecb0fa78957863221233b8e7d7cd8aa8da08eeb76c9e832bb783120

Observation 20e07c13-8263-4722-aca4-7cb180063ad5 · outbound

This paper cites Transformers4Rec: Bridging the gap be- tween nlp and sequential/session-based recommenda- tion.

A Survey on Sequential Recommendation Transformers4Rec: Bridging the gap be- tween nlp and sequential/session-based recommenda- tion

Reference 54

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source=pdf_text observed=2026-08-11T13:47:37.337037Z digest=sha256:14f711c438f1d88aaae2956a6104d04bcd9dff5178a3173d5150fb71d5b7b93b

Observation 64578dc9-a361-4af0-ba6c-5bc7feb4c553 · outbound

This paper cites Progressive self-attention network with unsymmetrical positional encoding for sequential recommendation.

A Survey on Sequential Recommendation Progressive self-attention network with unsymmetrical positional encoding for sequential recommendation

Reference 55

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source=pdf_text observed=2026-08-11T13:47:37.341722Z digest=sha256:632967533e04642450ce2d63a376ae5c48d962c5500759cac0033c37ab66c433

Observation 06e4b2fd-2fa8-495e-a300-f7e19650964a · outbound

This paper cites En- hancing Transformers without self-supervised learning: A loss landscape perspective in sequential recommen- dation.

A Survey on Sequential Recommendation En- hancing Transformers without self-supervised learning: A loss landscape perspective in sequential recommen- dation

Reference 56

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source=pdf_text observed=2026-08-11T13:47:37.346761Z digest=sha256:380ba1927b185a476160c289d6352551b613ba0f5f91f50d3e69ba27a8c36ab4

Observation d307121b-dcd2-4f07-9942-48a5ad2e703e · outbound

This paper cites Diffusion augmentation for sequential recommenda- tion.

A Survey on Sequential Recommendation Diffusion augmentation for sequential recommenda- tion

Reference 57

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source=pdf_text observed=2026-08-11T13:47:37.352089Z digest=sha256:e08965360a822da54786b7de12165d1f5cec6261db099513d94aa14b531f7bed

Observation c9232d03-98bd-4731-a60d-a37c5f10a498 · outbound

This paper cites Di ffuRec: A di ffusion model for sequential recommendation.

A Survey on Sequential Recommendation Di ffuRec: A di ffusion model for sequential recommendation

Reference 58

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source=pdf_text observed=2026-08-11T13:47:37.357729Z digest=sha256:25dfaeed8959ee0c9524282635afabaf580d483f56ffa24ccbf8efe428ecb00a

Observation 7bcd561a-f4e2-4edb-ba7c-3c03e2f764b7 · outbound

This paper cites Di ff4Rec: Sequential recommendation with curriculum-scheduled diffusion augmentation.

A Survey on Sequential Recommendation Di ff4Rec: Sequential recommendation with curriculum-scheduled diffusion augmentation

Reference 59

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source=pdf_text observed=2026-08-11T13:47:37.362574Z digest=sha256:d0501cecb9d13a2d6535ca2daeabaed54b8811f5ca599390e601daa1bbcf027a

Observation f79fd57f-ef96-4ce5-98b2-bcc545b60aea · outbound

This paper cites AutoSe- qRec: Autoencoder for efficient sequential recommen- dation.

A Survey on Sequential Recommendation AutoSe- qRec: Autoencoder for efficient sequential recommen- dation

Reference 60

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source=pdf_text observed=2026-08-11T13:47:37.367467Z digest=sha256:182d15250d54a2d812fb1ed4d7502953dedaf8416f2ff33b82f3bdcea2666fe6

Observation 1a87e46b-6847-46cb-b747-b46f2e2c550a · outbound

This paper cites Causality-driven user modeling for sequential recommendations over time.

A Survey on Sequential Recommendation Causality-driven user modeling for sequential recommendations over time

Reference 61

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source=pdf_text observed=2026-08-11T13:47:37.372586Z digest=sha256:3ab2ccaf2c103f507385cd08efe1c8d3dcefe81577f9d125a0512b489a00b441

Observation a1c5426c-f070-4cf5-bfd5-e04b4f95bc6b · outbound

This paper cites Leveraging two types of global graph for sequential fashion recom- mendation.

A Survey on Sequential Recommendation Leveraging two types of global graph for sequential fashion recom- mendation

Reference 62

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source=pdf_text observed=2026-08-11T13:47:37.377483Z digest=sha256:abf8b6aff13333a3665a2fde44d5bb35cc9238a5b8df2132b17ca741020a5c32

Observation 17c7b8d8-e6ba-4ccd-ac3a-57725b23a0df · outbound

This paper cites Modeling sequences as star graphs to address over-smoothing in self-attentive sequential recommendation.

A Survey on Sequential Recommendation Modeling sequences as star graphs to address over-smoothing in self-attentive sequential recommendation

Reference 63

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source=pdf_text observed=2026-08-11T13:47:37.382237Z digest=sha256:aefcbcb5c2a29d7617deee94d750f71f7709cc5c30fdb2238a83d2dbcde3cca5

Observation d075b27a-d94e-4fdd-8953-c4314a2e56d4 · outbound

This paper cites Filter-enhanced MLP is all you need for sequential recommendation.

A Survey on Sequential Recommendation Filter-enhanced MLP is all you need for sequential recommendation

Reference 64

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source=pdf_text observed=2026-08-11T13:47:37.386879Z digest=sha256:17f7b81c4cb0b206c1a1c5bcbf6bae97979dee45b005e0269b5a804293b6749c

Observation 0b0ebc82-cad5-4150-b0a9-67653f8b5b73 · outbound

This paper cites TriMLP: A foundational MLP-like archi- tecture for sequential recommendation.

A Survey on Sequential Recommendation TriMLP: A foundational MLP-like archi- tecture for sequential recommendation

Reference 65

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source=pdf_text observed=2026-08-11T13:47:37.391802Z digest=sha256:32f1cea14654eead78e607f3d2a59f36be9f283732119fffa5f26e335a5092f5

Observation fc315112-30bb-4257-bc29-3e20365f83a1 · outbound

This paper cites Learning global and multi-granularity local representation with MLP for sequential recommenda- tion.

A Survey on Sequential Recommendation Learning global and multi-granularity local representation with MLP for sequential recommenda- tion

Reference 66

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source=pdf_text observed=2026-08-11T13:47:37.397428Z digest=sha256:ae23cfc299612f9c1dd0082ab592834af26feff1a703d529f8ec4b7b7cdc827b

Observation 832b03c6-369a-45a1-a990-66ee75af4ecb · outbound

This paper cites Sequential variational autoencoders for collaborative filtering.

A Survey on Sequential Recommendation Sequential variational autoencoders for collaborative filtering

Reference 67

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source=pdf_text observed=2026-08-11T13:47:37.402057Z digest=sha256:d09ee592b385657b9e99fe0afaad322166ded25895ffe6cc67e569f1f47039d8

Observation e622053d-65c8-4f9e-861b-a1a822cbe470 · outbound

This paper cites Hierarchical temporal convolutional networks for dynamic recommender systems.

A Survey on Sequential Recommendation Hierarchical temporal convolutional networks for dynamic recommender systems

Reference 68

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source=pdf_text observed=2026-08-11T13:47:37.406793Z digest=sha256:ed0922f75f939295264f9b02eca4f950948c61396bff46188dadc7266bfc9048

Observation b64a4048-f9a6-4bb6-84d0-3df98fbbbf8f · outbound

This paper cites Gating aug- mented capsule network for sequential recommenda- tion.

A Survey on Sequential Recommendation Gating aug- mented capsule network for sequential recommenda- tion

Reference 69

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source=pdf_text observed=2026-08-11T13:47:37.411386Z digest=sha256:5d24febf8b41425dcfdff889cc8b6765474aa795125dad4cdaf9c878b78f16ab

Observation 19d193e7-5393-4180-885c-a08bb2afcc05 · outbound

This paper cites Time-aware multi-interest capsule network for sequential recommendation.

A Survey on Sequential Recommendation Time-aware multi-interest capsule network for sequential recommendation

Reference 70

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source=pdf_text observed=2026-08-11T13:47:37.416030Z digest=sha256:7db486a46d89cef838f7e4150c598c70e21031e67dab7cb65398bddd3101c916

Observation 92e5c650-1040-40fa-abe9-7a49d74d099d · outbound

This paper cites Deep Reinforcement Learning for List-wise Recommendations.

A Survey on Sequential Recommendation Deep Reinforcement Learning for List-wise Recommendations

Reference 71

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source=pdf_text observed=2026-08-11T13:47:37.420817Z digest=sha256:0e7def2d3fb2c138fa9f38985ecbe7ce1fcce6a66082885c0244ac08ef7e56fe

Observation d84ec406-325e-4b1f-91c5-1b263855e77d · outbound

This paper cites Sequence adaptation via re- inforcement learning in recommender systems.

A Survey on Sequential Recommendation Sequence adaptation via re- inforcement learning in recommender systems

Reference 72

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source=pdf_text observed=2026-08-11T13:47:37.425797Z digest=sha256:a7863af56fd668085f6e093169d54aea98feacc1c692445ddbe23213ac197765

Observation 5c391a69-a57f-4ac3-9513-f2cb7e969a11 · outbound

This paper cites AdaMCT: Adaptive mixture of CNN-Transformer for sequential recommendation.

A Survey on Sequential Recommendation AdaMCT: Adaptive mixture of CNN-Transformer for sequential recommendation

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source=pdf_text observed=2026-08-11T13:47:37.430638Z digest=sha256:d04333d21e2ebe6dd481f8b5eff5615c385e95263cb3d08cee5976ced3a6086a

Observation 633ce2ac-aea2-45ab-bad8-30fd3f7d4afc · outbound

This paper cites Towards accurate and interpretable sequential prediction: A CNN & attention- based feature extractor.

A Survey on Sequential Recommendation Towards accurate and interpretable sequential prediction: A CNN & attention- based feature extractor

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source=pdf_text observed=2026-08-11T13:47:37.435769Z digest=sha256:118b0838c15822b2e7ce86d18f19fe309869244b4a6e0358330be0cef5ed24b8

Observation fad55f29-8567-4df6-b95a-a2e87fa1a0c7 · outbound

This paper cites Learning to learn a cold-start sequential recommender.

A Survey on Sequential Recommendation Learning to learn a cold-start sequential recommender

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source=pdf_text observed=2026-08-11T13:47:37.440652Z digest=sha256:25eb6426c516f9d72bde048c7e66426f229d7f500b6da7a722e2c6c387a3c33c

Observation 046fe599-e130-4cd2-b180-8d38e5f26f30 · outbound

This paper cites Global- local graphformer: Towards better understanding of user intentions in sequential recommendation.

A Survey on Sequential Recommendation Global- local graphformer: Towards better understanding of user intentions in sequential recommendation

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source=pdf_text observed=2026-08-11T13:47:37.445710Z digest=sha256:00f938d1e40cd829147097e57b572ca69db336ad93743fe9ce50065f06298fb4

Observation 6a0a0fe9-b319-486c-8e5c-b369a6a4f8fe · outbound

This paper cites Graph masked autoencoder for sequential recommendation.

A Survey on Sequential Recommendation Graph masked autoencoder for sequential recommendation

Reference 77

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source=pdf_text observed=2026-08-11T13:47:37.450541Z digest=sha256:0d1ba99e202a313c207d36ff0c22d3aa7aa1bc98a25bb7aea3281a7f3b14471b

Observation 30b39cc8-6d17-45e7-accf-d6c32e216cc4 · outbound

This paper cites Learning from sub- stitutable and complementary relations for graph-based sequential product recommendation.

A Survey on Sequential Recommendation Learning from sub- stitutable and complementary relations for graph-based sequential product recommendation

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source=pdf_text observed=2026-08-11T13:47:37.455632Z digest=sha256:a3ab852ff3962608aed9bcc1dca81a9f46a231ee97a0a6935b740ea59ecc1c9b

Observation b7121450-f2e2-42b1-b04b-7e405464c5ee · outbound

This paper cites APGL4SR: A generic framework with adaptive and personalized global col- laborative information in sequential recommendation.

A Survey on Sequential Recommendation APGL4SR: A generic framework with adaptive and personalized global col- laborative information in sequential recommendation

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source=pdf_text observed=2026-08-11T13:47:37.460626Z digest=sha256:b340610a421cf8127fa865838e8f4623f7bbe081bce01e1297018e6d4c5ac6a9

Observation 9b796284-c1ba-46c5-b84a-799f8bab36b1 · outbound

This paper cites End-to-end graph-sequential representation learning for accurate recommendations.

A Survey on Sequential Recommendation End-to-end graph-sequential representation learning for accurate recommendations

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source=pdf_text observed=2026-08-11T13:47:37.465467Z digest=sha256:20ef13e4a648aa9a8762e432ab224f0e2f564a887f33230c5df31d2a7cb725b5

Observation 6215f6ff-6511-40b2-8838-ca60c2596858 · outbound

This paper cites Recurrent attentive neural networks for sequential recommendation.

A Survey on Sequential Recommendation Recurrent attentive neural networks for sequential recommendation

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.470387Z digest=sha256:f3a5b947b087c73896f3bf6f6f0c87dcf2d5fb8a1c8fbe0505080938915aac4c

Observation b2931f9e-8172-4d87-a9bf-cff734f52778 · outbound

This paper cites Sheng V S S, Cui Z, Zhou X, Xiong H.

A Survey on Sequential Recommendation Sheng V S S, Cui Z, Zhou X, Xiong H

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unresolved
no resolver link, observed 2026-08-11T13:47:37.475774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.475774Z digest=sha256:2e75fc7d65b643a342893dcdab199d5f40e4f8d97409e950a0972b16a71aefbe

Observation ae440b3a-a7ee-4fd2-b559-d1b8fe517ffb · outbound

This paper cites Learning neighbor user intention on user–item inter- action graphs for better sequential recommendation.

A Survey on Sequential Recommendation Learning neighbor user intention on user–item inter- action graphs for better sequential recommendation

Reference 83

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.481034Z digest=sha256:c3116e475bedf069c532bdc97cb39c55358e01c34e591cbc8d6aebd405a81c71

Observation ba5cac91-5ffc-4742-9fef-256eb09f7f27 · outbound

This paper cites an unresolved cited work.

A Survey on Sequential Recommendation Unresolved cited work

Reference 84

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unresolved
no resolver link, observed 2026-08-11T13:47:37.486367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9368b323-9e4b-4703-bb44-7aa8f14b2497 · outbound

This paper cites Cross-domain self-attentive sequential recommendations.

A Survey on Sequential Recommendation Cross-domain self-attentive sequential recommendations

Reference 85

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.491202Z digest=sha256:24ad6c13cc168e1120c82d5c552164459db1a644070fffd86224fd736d3694c2

Observation 256b4fe4-a633-4b5e-b5eb-4914b5c22783 · outbound

This paper cites Triple sequence learning for cross-domain recommen- dation.

A Survey on Sequential Recommendation Triple sequence learning for cross-domain recommen- dation

Reference 86

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.495833Z digest=sha256:9ebcaa347e930ff6a076870f487ff2ea9e7434ac0d1a1d5a6c920bbc79365a9c

Observation f81e69e9-cd32-4318-af2f-93d462f4b2a5 · outbound

This paper cites Contrastive cross-domain sequential recommendation.

A Survey on Sequential Recommendation Contrastive cross-domain sequential recommendation

Reference 87

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.500575Z digest=sha256:395e651d45c8bf8fa5f8813c90d14ce68839f83706b9d62a1d1af730ebc31e83

Observation 6629d5aa-0a17-47d9-822c-7f655c8b0e74 · outbound

This paper cites Time interval aware self- attention for sequential recommendation.

A Survey on Sequential Recommendation Time interval aware self- attention for sequential recommendation

Reference 88

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unresolved
no resolver link, observed 2026-08-11T13:47:37.505176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.505176Z digest=sha256:9f6907fdce389a422d12ca342859278b2ff5c2f1682f0c2a939f7bf85ae49bb1

Observation 6a7d5a0b-1f83-416f-b81c-1d999267072c · outbound

This paper cites Learning heteroge- neous temporal patterns of user preference for timely recommendation.

A Survey on Sequential Recommendation Learning heteroge- neous temporal patterns of user preference for timely recommendation

Reference 89

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.509870Z digest=sha256:36d12b6ac7f40ca61a97cead7890bc063fcf29eb4c6cc8e569ceafd7c155c0ae

Observation 619f1ce2-c9bc-4d98-a2a7-89ebc53c48c6 · outbound

This paper cites Multi- behavior sequential Transformer recommender.

A Survey on Sequential Recommendation Multi- behavior sequential Transformer recommender

Reference 90

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.514944Z digest=sha256:358fcb1d3d2d6135503bfb32bf77d3efcedee867e42f15eca36879030b97a1bd

Observation ac32121c-900b-47ce-94d2-6d2363f4a987 · outbound

This paper cites Person- alized behavior-aware Transformer for multi-behavior sequential recommendation.

A Survey on Sequential Recommendation Person- alized behavior-aware Transformer for multi-behavior sequential recommendation

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.520047Z digest=sha256:df75a4e3c39f553095ef2f9f2c9512307e6353d80c3bce455993a361ea3ea9e0

Observation 2362acec-e920-4651-ac3b-0d17a0993d70 · outbound

This paper cites Global heterogeneous graph and target interest denois- ing for multi-behavior sequential recommendation.

A Survey on Sequential Recommendation Global heterogeneous graph and target interest denois- ing for multi-behavior sequential recommendation

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.524809Z digest=sha256:e632f4ad36b6c99e8b24d1e0c43531d954bf242ce7aed2e7502706aae20e0c43

Observation 2a9a672d-3aeb-4f6d-b593-047722019dee · outbound

This paper cites Learning dual dynamic representations on time-sliced user-item interaction graphs for sequential recommendation.

A Survey on Sequential Recommendation Learning dual dynamic representations on time-sliced user-item interaction graphs for sequential recommendation

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no resolver link, observed 2026-08-11T13:47:37.529353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.529353Z digest=sha256:1d47ca3ea91591e12fad122033fbce4f4a156bd0e661d106840f583c6ff82b7a

Observation e8743a48-ef73-42ab-b405-c389a6623c46 · outbound

This paper cites Attention mixtures for time-aware sequential recom- Liwei Pan et al.

A Survey on Sequential Recommendation Attention mixtures for time-aware sequential recom- Liwei Pan et al

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source=pdf_text observed=2026-08-11T13:47:37.533802Z digest=sha256:444bfb09afdbd18f18c7269c959bf404fd770342d7bc6d523bd02df277207e3e

Observation fac1019b-4d87-4115-b2b3-4bee493cf6da · outbound

This paper cites Continuous-time sequential recommendation with tem- poral graph collaborative Transformer.

A Survey on Sequential Recommendation Continuous-time sequential recommendation with tem- poral graph collaborative Transformer

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.539014Z digest=sha256:95518e756e5aacc0b9b0305a52e858fb67e5f50d2178a552a9a8c7e8fb55a056

Observation 3a78c5b1-3d44-46a8-9849-2fda62cb208e · outbound

This paper cites Time interval-aware graph with self- attention for sequential recommendation.

A Survey on Sequential Recommendation Time interval-aware graph with self- attention for sequential recommendation

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.543788Z digest=sha256:d6ff8172259b606b5c4d44a152e735aa14570e661d46a04f111472933dbc3179

Observation 8e5ebf27-4c52-4b94-bf7b-233aaba31c71 · outbound

This paper cites Moving forward together: A multi-user pat- tern extraction neural model for sequential recommen- dations.

A Survey on Sequential Recommendation Moving forward together: A multi-user pat- tern extraction neural model for sequential recommen- dations

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T13:47:37.548897Z digest=sha256:f1a65c44c21c6dd7ea569f45b285d91b78cb35010a757a43f09aa82f6c62f0ab

Observation eb181d7e-0b3e-4390-8d8d-f782712276f3 · outbound

This paper cites Next- item recommendation with sequential hypergraphs.

A Survey on Sequential Recommendation Next- item recommendation with sequential hypergraphs

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:37.553872Z digest=sha256:ea55e98dbeaf871a8857ef8112f938e732acbcb8a053614eb192873a40b57ea0

Observation 9a880d99-986c-466b-9e57-39d2425b795c · outbound

This paper cites Position-enhanced and time-aware graph convolutional network for sequential recommendations.

A Survey on Sequential Recommendation Position-enhanced and time-aware graph convolutional network for sequential recommendations

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T13:47:37.558666Z digest=sha256:753364523e6eade7346651d55e2e7a8b1aea22ff3acdad5b6dea3671b94a4393

Observation 9e4784b1-6c46-4ad2-94a0-8d68480d8eeb · outbound

This paper cites Adaptive hier- archical translation-based sequential recommendation.

A Survey on Sequential Recommendation Adaptive hier- archical translation-based sequential recommendation

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source=pdf_text observed=2026-08-11T13:47:37.563307Z digest=sha256:bb95797e5e0ece774abb1b26ad468e9642f09b6a56ac02ce654a88678bcc8bd0

Pith citing papers

Observation 91f120a1-4072-4ffe-a788-de305dea21d6 · inbound

Unlocking the Power of Diffusion Models in Sequential Recommendation: A Simple and Effective Approach cites this paper.

Unlocking the Power of Diffusion Models in Sequential Recommendation: A Simple and Effective Approach A Survey on Sequential Recommendation

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no resolver link, observed 2026-08-07T14:16:33.881146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:16:33.881146Z digest=sha256:61c2778dbd7f85f1338a01a9533e57a0081647fa3ca5c166cabd563eb5213064

Observation 2b6cfc8c-42b7-4843-a28d-4f8a59a46d1d · inbound

Beyond Negative Transfer: Disentangled Preference-Guided Diffusion for Cross-Domain Sequential Recommendation cites this paper.

Beyond Negative Transfer: Disentangled Preference-Guided Diffusion for Cross-Domain Sequential Recommendation A Survey on Sequential Recommendation

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:42:46.205551Z digest=sha256:1ddfcca8d034515f4ed747e19243ce805c1f8cd99439ee020fb252e34422eb04

Observation 094b11d8-2e44-48a9-bef7-6f30217eb09a · inbound

Beyond Noisy Signals: Dual-Level Denoising for Multi-modal Sequential Recommendation cites this paper.

Beyond Noisy Signals: Dual-Level Denoising for Multi-modal Sequential Recommendation A Survey on Sequential Recommendation

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verified exact
local_arxiv, observed 2026-08-01T14:28:25.593501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-01T14:25:44.801466Z digest=sha256:cb21c8681e1264b70f42edd87444c831795a268246fe05e17c17a036a9fc1a04