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Paper Citation Record · LEDGER

Unifying Generative and Dense Retrieval for Sequential Recommendation

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2411.18814.

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

pith.paper-citation-record.v1
2411.18814 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:00:26.972723Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:00:06.171996Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 71704dfc-97fb-4156-984e-7f024dac8f4b · inbound

Augment or Not? A Comparative Study of Pure and Augmented Large Language Model Recommenders cites this paper.

Augment or Not? A Comparative Study of Pure and Augmented Large Language Model Recommenders Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:26.972723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:00:26.972723Z digest=sha256:07d3056bd5e4d6732d634e44f1ab51e1dfdc90801eed136ceac2e6a7fff25504

Observation 30c4e3cb-512e-4d7e-9802-c7ac3a931207 · inbound

Generating Long Semantic IDs in Parallel for Recommendation cites this paper.

Generating Long Semantic IDs in Parallel for Recommendation Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T10:21:54.276270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:54.276270Z digest=sha256:66c31c625252593f59e14abd689bc337b98ecce190d083f640353f97b9624d77

Observation eac8234f-e163-4fb6-973a-70287d790008 · inbound

GR-LLMs: Recent Advances in Generative Recommendation Based on Large Language Models cites this paper.

GR-LLMs: Recent Advances in Generative Recommendation Based on Large Language Models Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-06T19:06:06.952470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:06:06.952470Z digest=sha256:93ad30d03522796500da412a52c2cd76f74ca06728f0099d54d5d2e27e10a2b9

Observation e8953740-6668-48b8-8ec8-f9618b214890 · inbound

Generative Recommendation with Semantic IDs: A Practitioner's Handbook cites this paper.

Generative Recommendation with Semantic IDs: A Practitioner's Handbook Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 61

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unresolved
no resolver link, observed 2026-08-06T12:01:13.384482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:01:13.384482Z digest=sha256:ae3b9bc56b101ae3aa1bcd7676bda1040eb5ff542152fed45d774741cc905ef0

Observation 71ab3836-dd78-4f72-81b6-293ba4099882 · inbound

Sequential Data Augmentation for Generative Recommendation cites this paper.

Sequential Data Augmentation for Generative Recommendation Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-21T22:44:24.362467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T22:43:37.684798Z digest=sha256:1d0768779027d071fd04dc0f349f19a658a05d87aaec7ffe9fff8652acfa5546

Observation 214e1b4e-2a85-4abd-a8a9-17612208af5b · inbound

FORGE: Forming Semantic Identifiers for Generative Retrieval in Industrial Datasets cites this paper.

FORGE: Forming Semantic Identifiers for Generative Retrieval in Industrial Datasets Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-04T15:17:07.626367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T15:17:07.626367Z digest=sha256:5307592a60573a22611202d80878b7d08f8e9355388e45c31ad7cf2edc4f2a03

Observation 62bc7a19-aa42-4dcd-9045-0462e3f7cf28 · inbound

GenRecEdit: Adapting Model Editing for Generative Recommendation with Cold-Start Items cites this paper.

GenRecEdit: Adapting Model Editing for Generative Recommendation with Cold-Start Items Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-15T11:55:33.413631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T11:53:25.713932Z digest=sha256:20de0c7959102b58f49fe323f5ca1a2625a41d5b50ca604a46f37af182422b96

Observation a0024a4f-5d05-4962-a158-fba8adb4ee43 · inbound

Semantic IDs for Recommender Systems at Snapchat: Use Cases, Technical Challenges, and Design Choices cites this paper.

Semantic IDs for Recommender Systems at Snapchat: Use Cases, Technical Challenges, and Design Choices Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 41

Resolution
unresolved
no resolver link, observed 2026-07-13T11:47:58.173367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T11:47:58.173367Z digest=sha256:3781cdfc2576cd44b078e9d767d09d509f9503188e677be79b0d4c754f23e5c8

Observation 6b53f95e-ac9e-4024-adda-98ea499cf1ff · inbound

Mitigating Collaborative Semantic ID Staleness in Generative Retrieval cites this paper.

Mitigating Collaborative Semantic ID Staleness in Generative Retrieval Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-10T14:00:29.465419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T13:55:29.531937Z digest=sha256:e511fa472a43cfbb5dfba04b1e4d8c0fff2c20a1f142ab71f9901dda1915f0c4

Observation 582070c6-97c7-43f9-bb2b-1c12abb91bcb · inbound

MTServe: Efficient Serving for Generative Recommendation Models with Hierarchical Caches cites this paper.

MTServe: Efficient Serving for Generative Recommendation Models with Hierarchical Caches Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:16:07.688605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T12:28:21.346963Z digest=sha256:989f65da24b7f49f35cf37f3e75eab067a5f1609b269315b2ecf202c33ba31ba

Observation 76ea22f0-cb55-4c29-a0cb-74a8e458975b · inbound

CapsID: Soft-Routed Variable-Length Semantic IDs for Generative Recommendation cites this paper.

CapsID: Soft-Routed Variable-Length Semantic IDs for Generative Recommendation Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:26:12.829000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T15:54:53.821143Z digest=sha256:d7800312453acb7305a08a06633c67f94bdf291efd3fa9df2fda78c04bf59c13

Observation 44dab3d1-6ecd-4ed8-96a8-fabe33193c50 · inbound

Expressiveness Limits of Autoregressive Semantic ID Generation in Generative Recommendation cites this paper.

Expressiveness Limits of Autoregressive Semantic ID Generation in Generative Recommendation Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:21:12.643115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T05:49:16.718963Z digest=sha256:0c1a6c1681cdc648b426d0d91f35126055658ae35b282303a57401b1e245fdb6

Observation 2b6307b7-78af-420d-be0d-f9e34668f013 · inbound

Bridging Textual Profiles and Latent User Embeddings for Personalization cites this paper.

Bridging Textual Profiles and Latent User Embeddings for Personalization Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:50:56.736262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:02:49.813751Z digest=sha256:687c214ac8a429f9d49620a292d73635e4e0f97962b04b7572c1db912a240524

Observation 9938809f-5381-4834-a9bc-8080031abcbb · inbound

Conditional Memory Enhanced Item Representation for Generative Recommendation cites this paper.

Conditional Memory Enhanced Item Representation for Generative Recommendation Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-13T02:32:06.297649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-13T02:30:29.654122Z digest=sha256:7f0e0c3015901a9329dfa27c9a95819713b110ee10c22c48c5aba7e77d363ad4

Observation 70d84121-745e-46f6-af35-c21c118f3b5c · inbound

MLPs are Efficient Distilled Generative Recommenders cites this paper.

MLPs are Efficient Distilled Generative Recommenders Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-14T20:19:28.230894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-14T20:14:52.127606Z digest=sha256:02613c3fbc361feb867ca3346f9cf6fa968a5548189e5760b23338fa65ebd412

Observation 5e7c6a1b-8f16-4497-944f-6bd411de6df7 · inbound

LWGR: Lagrangian-Constrained Personalized World Knowledge for Generative Recommendation cites this paper.

LWGR: Lagrangian-Constrained Personalized World Knowledge for Generative Recommendation Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-21T01:33:56.572879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T01:30:03.878197Z digest=sha256:56a35b8ace64f7adac92bdcf4955e9cd87d35a649ea70b56b98e917cc5e43be8

Observation ce614079-b44f-4054-80da-a40b49e5a7d6 · inbound

UniPinRec: Unifying Generative Retrieval and Ranking at Pinterest Scale cites this paper.

UniPinRec: Unifying Generative Retrieval and Ranking at Pinterest Scale Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T20:32:37.231417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 56688349-c8f9-4abc-8dda-4e51b359fcbd · inbound

TokenMinds: Pretrained User Tokens and Embeddings for User Understanding in Large Recommender Systems cites this paper.

TokenMinds: Pretrained User Tokens and Embeddings for User Understanding in Large Recommender Systems Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-07-04T19:00:06.175113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-25T22:00:13.334443Z digest=sha256:be0f875137df63cd5b8d189ca97216c3e2c7b591188c00d49db8e9a6349c46e9

Observation d7fd06b4-ea2e-40e0-9df8-0b7ad80f8b2f · inbound

Beyond Item Order: Temporal Gap Tokenization for Generative Recommendation with Semantic IDs cites this paper.

Beyond Item Order: Temporal Gap Tokenization for Generative Recommendation with Semantic IDs Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-07-11T23:02:18.007239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T23:02:18.007239Z digest=sha256:262635fd5520894b6b4dc82c8f1a47f4f38d1a43c8965e5269edfd218831c10b

Observation 54098a08-8e93-4666-a14a-070f805550d9 · inbound

From Understanding to Action: Feedback-Grounded Policy Discovery for Generative Recommendation cites this paper.

From Understanding to Action: Feedback-Grounded Policy Discovery for Generative Recommendation Unifying Generative and Dense Retrieval for Sequential Recommendation

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-01T01:28:22.073426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T01:28:22.073426Z digest=sha256:4c75cf9a0eb828151d004531d78762e7a672a9d5966f03fce204ffb871a439b1