Paper Citation Record · LEDGER

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation

As of 16 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 2 inbound Pith citation observations for arXiv:2506.16683.

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

pith.paper-citation-record.v1
2506.16683 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:26:33.454588Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-16T10:54:59.933205Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T10:57:46.391040Z

Reference resolution

56 of 56 outbound references displayed

verified exact0
verified fuzzy43
unresolved13
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fb2da073-0db9-4ec0-ad6b-799e8eb7aa63 · outbound

This paper cites Deep neural networks for youtube recommendations,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Deep neural networks for youtube recommendations,

Reference 1

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Source-reported events for the cited work

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Observation 8d3ec8dc-1326-4c39-bfc7-7149c7c4e671 · outbound

This paper cites The netflix recommender system: Algorithms, business value, and innovation,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation The netflix recommender system: Algorithms, business value, and innovation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.313653Z

Source-reported events for the cited work

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Observation ea651716-9f82-4ad1-9ea3-69340830b5cf · outbound

This paper cites A review of modern recommender systems using generative models (gen-recsys),.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation A review of modern recommender systems using generative models (gen-recsys),

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.298634Z

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Observation 24c3b5a1-e960-424d-a00b-a5d915d7f777 · outbound

This paper cites Attention is all you need,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Attention is all you need,

Reference 4

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Observation 299e73f0-8558-494c-b605-183243c3af51 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.273111Z

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Observation af4cc65c-67dd-4f3e-95fa-4c0ee686faea · outbound

This paper cites Sequence to sequence learning with neural networks,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Sequence to sequence learning with neural networks,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.259030Z

Source-reported events for the cited work

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Observation 9ac60754-2afc-4a21-9cd2-f0aac5aeef4e · outbound

This paper cites Recommender systems with generative retrieval,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Recommender systems with generative retrieval,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.244733Z

Source-reported events for the cited work

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Observation 80573162-a4a8-4fdd-8d35-2870d10e82a2 · outbound

This paper cites Better general- ization with semantic ids: A case study in ranking for recommendations,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Better general- ization with semantic ids: A case study in ranking for recommendations,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.230193Z

Source-reported events for the cited work

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Observation 99af1dd0-3524-4a75-8f9c-eafcefa653e3 · outbound

This paper cites Vector Quantization for Recommender Systems: A Review and Outlook.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Vector Quantization for Recommender Systems: A Review and Outlook

Reference 9

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Observation 8682aa97-c0d3-4236-be0d-b4b2ce61faf0 · outbound

This paper cites Recommender forest for efficient retrieval,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Recommender forest for efficient retrieval,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.215508Z

Source-reported events for the cited work

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Observation d23f0b3d-b104-4d20-a1c9-f38f13d7460d · outbound

This paper cites Eager: Two-stream generative recommender with behavior-semantic collaboration,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Eager: Two-stream generative recommender with behavior-semantic collaboration,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.200711Z

Source-reported events for the cited work

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Observation 55ce6ece-b753-44b7-8926-c6c594fc72c8 · outbound

This paper cites Transformer memory as a differentiable search index,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Transformer memory as a differentiable search index,

Reference 12

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Source-reported events for the cited work

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Observation d6d953b5-26c7-4c0b-ac7e-d15c2559f15e · outbound

This paper cites Cost: Contrastive quantization based semantic tokenization for generative recommenda- tion,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Cost: Contrastive quantization based semantic tokenization for generative recommenda- tion,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.169167Z

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Observation 376a7253-3c9c-4093-8f6b-795c21b8ca75 · outbound

This paper cites Learnable item tokenization for generative recommendation,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Learnable item tokenization for generative recommendation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.153544Z

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Observation 26dae1c0-b66b-4ad1-8129-fbd220adc644 · outbound

This paper cites Where to go next: A spatio-temporal gated network for next poi recommendation,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Where to go next: A spatio-temporal gated network for next poi recommendation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.138389Z

Source-reported events for the cited work

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Observation 5f1df018-639d-41c6-8e9e-199a64e06371 · outbound

This paper cites Spatio-temporal hypergraph learning for next poi recommendation,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Spatio-temporal hypergraph learning for next poi recommendation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.122770Z

Source-reported events for the cited work

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Observation ff44e13c-4c29-48aa-b6c3-053d92d86f80 · outbound

This paper cites Unifying Generative and Dense Retrieval for Sequential Recommendation.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T19:26:33.274112Z

Source-reported events for the cited work

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Observation 43621ea5-cebe-4aec-82ba-3d0c86ec6a9f · outbound

This paper cites OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T19:26:33.279089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d333d4f-5289-4e4f-9640-cfff1999b9f7 · outbound

This paper cites Understanding differential search index for text retrieval,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Understanding differential search index for text retrieval,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.106720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 74c5664f-5b26-4b40-9403-a8a2e8c3e939 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Direct preference optimization: Your language model is secretly a reward model,

Reference 20

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Source-reported events for the cited work

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Observation 35d3454d-2f44-4dfd-ade8-f61a78900e59 · outbound

This paper cites Tokenrec: Learning to tokenize id for llm-based generative recommendation,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Tokenrec: Learning to tokenize id for llm-based generative recommendation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.079766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 76024231-c40f-4288-81d7-bdc3fad8f160 · outbound

This paper cites How to index item ids for recommendation foundation models,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation How to index item ids for recommendation foundation models,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.064557Z

Source-reported events for the cited work

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Observation ecfcfe2c-4464-4e5e-979e-33d55d63cad9 · outbound

This paper cites Recommendation as language processing (rlp): A unified pretrain, personalized prompt & predict paradigm (p5),.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Recommendation as language processing (rlp): A unified pretrain, personalized prompt & predict paradigm (p5),

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.047967Z

Source-reported events for the cited work

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Observation 190ab852-95ad-479d-b3c2-500b696aaad8 · outbound

This paper cites Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation

Reference 24

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Source-reported events for the cited work

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Observation 3bcf9752-b767-4b98-962a-63339002389f · outbound

This paper cites Learning transferable visual models from natural language supervi- sion,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Learning transferable visual models from natural language supervi- sion,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T19:26:33.311681Z

Source-reported events for the cited work

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Observation ce2014b0-3b1a-4e8b-bcfc-382bc4876e2b · outbound

This paper cites FLA V A: A foundational language and vision alignment model,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation FLA V A: A foundational language and vision alignment model,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:34.019467Z

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Observation a68e4b6e-fb8a-404a-869b-ebf8a6ecb88f · outbound

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Perceiver: General perception with iterative attention,

Reference 27

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Source-reported events for the cited work

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Observation 7527eaf5-5022-4ee1-8d38-c8328d5288cd · outbound

This paper cites Iisan: Efficiently adapting multimodal representation for sequen- tial recommendation with decoupled peft,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Iisan: Efficiently adapting multimodal representation for sequen- tial recommendation with decoupled peft,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.988619Z

Source-reported events for the cited work

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Observation 73e96bf3-57fc-432b-978a-0d65cc2459d3 · outbound

This paper cites Multi-modal knowledge graphs for recommender systems,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Multi-modal knowledge graphs for recommender systems,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.973458Z

Source-reported events for the cited work

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Observation f55a24a4-f6f9-4bdb-8ec1-8ad46ec74179 · outbound

This paper cites Mining latent structures for multimedia recommendation,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Mining latent structures for multimedia recommendation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.957972Z

Source-reported events for the cited work

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Observation 07362e6f-e632-4300-8055-d38c5cbc15e2 · outbound

This paper cites Dualgnn: Dual graph neural network for multimedia recommendation,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Dualgnn: Dual graph neural network for multimedia recommendation,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.942288Z

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Observation 6278e85e-530f-48f7-9be6-0ec4bc179d13 · outbound

This paper cites Multimodal Quantitative Language for Generative Recommendation.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Multimodal Quantitative Language for Generative Recommendation

Reference 32

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation MMGRec: Multimodal Generative Recommendation with Transformer Model

Reference 33

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This paper cites Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics

Reference 34

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation A simple framework for contrastive learning of visual representations,

Reference 35

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Observation ad69b466-c169-4e93-ba7d-f5042d1c99a1 · outbound

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Momentum Contrast for Unsupervised Visual Representation Learning ,

Reference 36

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Observation a0b55e61-5559-4089-8a9c-45abfc94fc6c · outbound

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Contrastive quantiza- tion with code memory for unsupervised image retrieval,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.893875Z

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Self-supervised graph learning for recommendation,

Reference 38

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Observation cba2bcac-8767-4dc0-ba09-44e28e8647e0 · outbound

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Multimodal contrastive transformer for explainable recommendation,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.862588Z

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Contrastive multimodal fusion with tupleinfonce,

Reference 40

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Understanding the robustness of multi-modal contrastive learning to distribution shift,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.837768Z

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation What makes for good views for contrastive learning?

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.822282Z

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Observation 3cf54585-4487-469a-a647-86d80f997a0e · outbound

This paper cites On Mutual Information in Contrastive Learning for Visual Representations.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation On Mutual Information in Contrastive Learning for Visual Representations

Reference 43

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Inductive representation learning on large graphs,

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This paper cites Categorical reparameterization with gumbel-softmax,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Categorical reparameterization with gumbel-softmax,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.791275Z

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A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation A review of the gumbel-max trick and its extensions for discrete stochas- ticity in machine learning,

Reference 47

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Observation 891d17c9-1db4-48e2-8d95-158389838fa4 · outbound

This paper cites Justifying recommendations using distantly-labeled reviews and fine-grained aspects,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Justifying recommendations using distantly-labeled reviews and fine-grained aspects,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.759741Z

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Observation 670a6600-8fb2-4dbb-8377-68c15564791d · outbound

This paper cites Modeling user activity preference by leveraging user spatial temporal characteristics in lbsns,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Modeling user activity preference by leveraging user spatial temporal characteristics in lbsns,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.744349Z

Source-reported events for the cited work

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Observation cac132e9-12e6-4ab4-b7a6-16219f7ffd0b · outbound

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

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Session-based recommendations with recurrent neural networks,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.729110Z

Source-reported events for the cited work

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Observation a8fc5e0a-3c40-4808-ba75-dd414fec4b36 · outbound

This paper cites Self-attentive sequential recommenda- tion,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Self-attentive sequential recommenda- tion,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.713115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e8cba020-ea54-4490-9084-7459544bf6fc · outbound

This paper cites Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.696992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dea88442-96eb-447d-ac95-f39b4eaf8c0c · outbound

This paper cites Stan: Spatio-temporal attention network for next location recommendation,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Stan: Spatio-temporal attention network for next location recommendation,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.681986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4101e91a-af0f-4b63-ae74-b1d6b4eb3588 · outbound

This paper cites Alternating least squares for personalized ranking,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Alternating least squares for personalized ranking,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.666790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 93a09d0e-a6f4-4c37-afbd-b08d5b93da52 · outbound

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

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Fast matrix factorization for online recommendation with implicit feedback,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.652015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 678ad23f-78b4-4b0b-ae84-dbfc12d6de43 · outbound

This paper cites Understanding and improving the role of projection head in self-supervised learning,.

A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation Understanding and improving the role of projection head in self-supervised learning,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:26:33.636542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation 5424ef7d-179e-40dd-8b4b-0a4a340d39d2 · inbound

Differentiable Semantic ID for Generative Recommendation cites this paper.

Differentiable Semantic ID for Generative Recommendation A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-16T10:57:46.393517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1a6e68ce-cb2f-4cd7-9aff-b6833c27e675 · inbound

MLPs are Efficient Distilled Generative Recommenders cites this paper.

MLPs are Efficient Distilled Generative Recommenders A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:19:28.236686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.