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Paper Citation Record · LEDGER

A Survey of Generative Search and Recommendation in the Era of Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 28 inbound Pith citation observations for arXiv:2404.16924.

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

pith.paper-citation-record.v1
2404.16924 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:31:18.263924Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T07:37:45.509556Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
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  • malformed identifier0
  • metadata mismatch0

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 2257fca9-a87e-40c6-908c-738f8e144e18 · inbound

NExT-Search: Rebuilding User Feedback Ecosystem for Generative AI Search cites this paper.

NExT-Search: Rebuilding User Feedback Ecosystem for Generative AI Search A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 26

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no resolver link, observed 2026-08-07T15:31:18.263924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:31:18.263924Z digest=sha256:6f185cbd08a48d0e0850e7fa60fc0b5cf07042f48a9872ed5c214bb29806f5eb

Observation 56126050-6403-4755-a38e-69fd8989c7ce · inbound

GRAM: Generative Recommendation via Semantic-aware Multi-granular Late Fusion cites this paper.

GRAM: Generative Recommendation via Semantic-aware Multi-granular Late Fusion A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 31

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no resolver link, observed 2026-08-07T11:42:09.450235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:42:09.450235Z digest=sha256:4d3873c960e40ae93a37d87b8b47be628653c53eb034048839d354796925d558

Observation 74fcc427-5a90-4dba-a666-f4bce252991b · inbound

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

Generating Long Semantic IDs in Parallel for Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 26

Resolution
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no resolver link, observed 2026-08-07T10:21:54.170513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:54.170513Z digest=sha256:313b9ddf3b6f0a5662ff8d94dfbbb26da947aa158fa60382a9faa4fdb7d4708b

Observation 53cfde24-6e9e-414f-a4b8-694f1d16010f · inbound

GFlowGR: Fine-tuning Generative Recommendation Frameworks with Generative Flow Networks cites this paper.

GFlowGR: Fine-tuning Generative Recommendation Frameworks with Generative Flow Networks A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 24

Resolution
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no resolver link, observed 2026-08-06T23:49:15.305212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:15.305212Z digest=sha256:015231b17812e390aadc09d4174d9a8fc0e7c852f0f5cc2b2ee682cd5d723044

Observation 289bf4b2-16c7-418a-a59f-fdc77918067c · inbound

EARN: Efficient Inference Acceleration for LLM-based Generative Recommendation by Register Tokens cites this paper.

EARN: Efficient Inference Acceleration for LLM-based Generative Recommendation by Register Tokens A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T21:18:47.782126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:18:47.782126Z digest=sha256:eed696240e7f20302ebbed4e3c4b9f0160382cadf2171f566906a85951f6527f

Observation 537fdb26-9260-4a41-98d5-849d3456c93c · inbound

Optimizing Conversational Product Recommendation via Reinforcement Learning cites this paper.

Optimizing Conversational Product Recommendation via Reinforcement Learning A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T21:45:46.880568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:45:46.880568Z digest=sha256:619400c8f8e763d9930240cece2e0b444b2d38b5282d8275e9c72d96e6506d1a

Observation 486eec6f-2e5d-446b-8231-e3e76c0c556d · inbound

Heterogeneous User Modeling for LLM-based Recommendation cites this paper.

Heterogeneous User Modeling for LLM-based Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 17

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no resolver link, observed 2026-08-06T19:48:14.123097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:48:14.123097Z digest=sha256:bd145ab4f3729f7cdb81133708f536dd144f655fe01d619ff1ec8889c3cc4d62

Observation 20673f78-49ef-475c-95d5-990c02a5ada6 · inbound

Brownian Bridge Diffusion for Sequential Recommendation cites this paper.

Brownian Bridge Diffusion for Sequential Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-19T05:57:08.356220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T05:53:22.577986Z digest=sha256:81be0b8fdb43d037358fce9490cc7d123707a15a09eee91a1fdaea030c9424c0

Observation a0ccc43f-1ea6-4601-bf7b-848598c86a29 · 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 A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 46

Resolution
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no resolver link, observed 2026-08-06T19:06:04.530230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:06:04.530230Z digest=sha256:bb501712654d3cfb494ea9685ad975097415493b3bb4d2d0683153a133d0ab41

Observation cce92320-e785-4aab-a005-0bf006bda2b4 · inbound

Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning cites this paper.

Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 18

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no resolver link, observed 2026-08-06T18:54:14.763580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:54:14.763580Z digest=sha256:3708682fa76f72a2d88f384d1e27b7d573248bdef34ba9ebdc628e273912fa97

Observation 2b61443e-7819-4a09-9d7c-2982a74fd24b · inbound

Generative Multi-Target Cross-Domain Recommendation cites this paper.

Generative Multi-Target Cross-Domain Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 31

Resolution
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no resolver link, observed 2026-08-06T16:41:38.586292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:41:38.586292Z digest=sha256:e622ca27dc28b1832de5c374fc7e74bf436ffd65bebb75a4e5b0f4b0c67b19f0

Observation b65de2a5-3dfe-497a-805a-14bbe9d2336c · inbound

SSRL: Self-Search Reinforcement Learning cites this paper.

SSRL: Self-Search Reinforcement Learning A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 30

Resolution
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no resolver link, observed 2026-08-05T20:17:10.345154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:17:10.345154Z digest=sha256:33fdc509c860c7ff579fc2ee49f1231b9feebe22b56c2727b88b1cf0ba0a69cf

Observation 24e6e959-3f8c-44bc-9e30-ec7b7bc89ff5 · inbound

End-to-End Semantic ID Generation for Generative Advertisement Recommendation cites this paper.

End-to-End Semantic ID Generation for Generative Advertisement Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-22T11:54:51.409056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T11:51:53.936922Z digest=sha256:1561fca36456fcb42ebad3d5162b0d61e936062d611d3733491b6baba8b7fbd2

Observation 9e79b8b3-8690-41c9-83b5-7081df45dfc2 · inbound

DeepInterestGR: Mining Deep Multi-Interest Using Multi-Modal LLMs for Generative Recommendation cites this paper.

DeepInterestGR: Mining Deep Multi-Interest Using Multi-Modal LLMs for Generative Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 15

Resolution
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no resolver link, observed 2026-08-02T21:52:31.463022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:52:31.463022Z digest=sha256:97b8c9a822d15aa0039afbcae739b0862e5633b7c981e5740d1fa089b6b38d4f

Observation 97e38336-33ec-44b1-ab50-b072a02ea8c1 · inbound

Deep Interest Mining for Intent-Enriched Semantic IDs in Multimodal Generative Recommendation cites this paper.

Deep Interest Mining for Intent-Enriched Semantic IDs in Multimodal Generative Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-15T17:01:18.537925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T17:01:07.245161Z digest=sha256:540a305255ad4f6a38df65bbb16e64e01cb6206236936f1088674e438243b96c

Observation 8d714e87-7ba9-46b4-a64b-ed93170bf25e · inbound

Deep Interest Mining for Intent-Enriched Semantic IDs in Multimodal Generative Recommendation cites this paper.

Deep Interest Mining for Intent-Enriched Semantic IDs in Multimodal Generative Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-02T19:15:40.982227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T19:15:40.982227Z digest=sha256:c3531f84fee40e9c134c532d2f6265f1091fe2eb7b9a0cbbaf3262db5cffc4a3

Observation 4609c5b4-9510-4564-a9fa-ffee20479155 · inbound

Action-Aware Generative Sequence Modeling for Short Video Recommendation cites this paper.

Action-Aware Generative Sequence Modeling for Short Video Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:46:40.217331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T16:20:39.024412Z digest=sha256:e09490047003f555bc7fb4c4d8c6b416fae1f895fc46947c132dcfea948bb14b

Observation a8a13331-78a9-40b3-aa1d-647a452aeac3 · inbound

TriAlignGR: Triangular Multitask Alignment with Multimodal Deep Interest Mining for Generative Recommendation cites this paper.

TriAlignGR: Triangular Multitask Alignment with Multimodal Deep Interest Mining for Generative Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:10:43.296866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T18:46:08.393219Z digest=sha256:934566d425d1f29ea1ebe19cd3e7cd57fd07cf6d1b3612217fa107a9b4e324bd

Observation b4c7d9ae-fa34-4788-8fd9-f1be33797fbe · inbound

TriAlignGR: Triangular Multitask Alignment with Multimodal Deep Interest Mining for Generative Recommendation cites this paper.

TriAlignGR: Triangular Multitask Alignment with Multimodal Deep Interest Mining for Generative Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-20T23:53:51.804427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T23:50:47.510019Z digest=sha256:64c5be6e5d76adeb425cfccd3df46191089c0d5c87f6cbbb09ff37b6a7994f08

Observation e0d54455-f56b-40c7-bd06-c77e3172c3b7 · inbound

TriAlignGR: Triangular Multitask Alignment with Multimodal Deep Interest Mining for Generative Recommendation cites this paper.

TriAlignGR: Triangular Multitask Alignment with Multimodal Deep Interest Mining for Generative Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-07-01T00:15:09.161279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-01T00:12:24.019383Z digest=sha256:66d328ae927de8cf9a60363376e888d73dfb424570624723d185b513829f186b

Observation b3234a33-4594-4aaa-bd58-cab06cca5b15 · inbound

UniVA: Unified Value Alignment for Generative Recommendation in Online Advertising at Tencent cites this paper.

UniVA: Unified Value Alignment for Generative Recommendation in Online Advertising at Tencent A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:16:26.133229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T06:06:49.422159Z digest=sha256:d717181817aa9565587f19eebf93db1511b77a1cfaaac84f523c3268a0c51491

Observation 5ba8ce5f-31e0-4c54-bdec-f40a58b1eb69 · inbound

UniVA: Unified Value Alignment for Generative Recommendation in Online Advertising at Tencent cites this paper.

UniVA: Unified Value Alignment for Generative Recommendation in Online Advertising at Tencent A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-02T14:47:54.877541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:47:54.877541Z digest=sha256:214682af9cfb4a949ed449824da3ffba46b65f15109096431641e859ff03ee9a

Observation 2b5e6b4c-45b7-4c70-961f-ebba48c17d1e · inbound

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

Conditional Memory Enhanced Item Representation for Generative Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-13T02:32:06.287163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T02:30:29.654122Z digest=sha256:85bee11cd894a244d0b1f5a4c0f3327a7bfc705ace9f60d3f0f85460eb6b8d68

Observation 9137829e-d336-4812-b27d-3520b140fb38 · inbound

Efficient Generative Retrieval for E-commerce Search with Semantic Cluster IDs and Expert-Guided RL cites this paper.

Efficient Generative Retrieval for E-commerce Search with Semantic Cluster IDs and Expert-Guided RL A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:18:31.073486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T02:16:25.272764Z digest=sha256:4deade8049eb08de3ea432501207bf89e7e610a5985edec12f363672b8d04b16

Observation d7c4a422-58b0-497f-be6c-5a0675e0a51c · inbound

The 2nd EReL@MIR Workshop on Efficient Representation Learning for Multimodal Information Retrieval cites this paper.

The 2nd EReL@MIR Workshop on Efficient Representation Learning for Multimodal Information Retrieval A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-06-29T16:23:39.946265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T15:49:45.212333Z digest=sha256:581d921a0e56062d7d390d2d8a97d32f934295c440b1bbd74af59f4c702fd942

Observation 04e224f6-4793-47ef-b744-d953efe19c90 · inbound

SIDInspector: A Mapping-First Diagnostic Resource for Semantic-ID Tokenizers cites this paper.

SIDInspector: A Mapping-First Diagnostic Resource for Semantic-ID Tokenizers A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-03T07:37:45.510972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T11:56:50.401811Z digest=sha256:461e4c2eac4d6fdc52d0d07578f9b30182f37a6e92c0a27a34df30451a970611

Observation 4800448c-89e9-4341-b982-2d23097a5326 · inbound

Bridging the Structural Gap: Adapting Autoregressive Generation for Recommendation cites this paper.

Bridging the Structural Gap: Adapting Autoregressive Generation for Recommendation A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-01T08:44:51.550618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T08:44:51.550618Z digest=sha256:cad7b8fe70fd5f2a3ca08af0960fda047ac191b26d3a18070ae8f672f6b8ebec

Observation b0d95deb-47d1-4fb0-a497-d357956a5004 · inbound

GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models cites this paper.

GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models A Survey of Generative Search and Recommendation in the Era of Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-02T12:15:44.726281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:15:44.726281Z digest=sha256:64349bdb5712810e010cc018c5a03079fbc93fd5b25b2bdff5b58e0c11da4c11