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Paper Citation Record · LEDGER

A Survey on Large Language Models for Recommendation

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2305.19860.

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

pith.paper-citation-record.v1
2305.19860 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:37:17.453027Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T11:45:46.922574Z

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 330c7e3e-f0bb-4bb4-b473-af18a3181581 · inbound

A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation cites this paper.

A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation A Survey on Large Language Models for Recommendation

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-19T09:32:16.610016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-19T09:28:32.185398Z digest=sha256:4649d5785392033ace8d5f2b4bcc1cf42c4a5ddd6fddc6fae726e4b6e146e0bd

Observation bca64cd1-4567-4c8a-88ab-f4a31a51eab4 · inbound

Beyond Semantic Understanding: Preserving Collaborative Frequency Components in LLM-based Recommendation cites this paper.

Beyond Semantic Understanding: Preserving Collaborative Frequency Components in LLM-based Recommendation A Survey on Large Language Models for Recommendation

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-05T20:37:17.453027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:37:17.453027Z digest=sha256:6a9db01f291fa24b99b6ae900378eb5ff76bdae219bd77678335654a0f00849b

Observation d869d6cf-7765-4458-b938-a29796c12221 · inbound

TrackRec: Iterative Alternating Feedback with Chain-of-Thought via Preference Alignment for Recommendation cites this paper.

TrackRec: Iterative Alternating Feedback with Chain-of-Thought via Preference Alignment for Recommendation A Survey on Large Language Models for Recommendation

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-05T18:02:16.907452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:02:16.907452Z digest=sha256:bd5d9fdd52fa1d40bb78553b903c832411df9f64f66637b8a438069e01da4dfc

Observation 86ab4ce1-362a-4558-a12e-97d02306d2b7 · inbound

Understanding Generative Recommendation with Semantic IDs from a Model-scaling View cites this paper.

Understanding Generative Recommendation with Semantic IDs from a Model-scaling View A Survey on Large Language Models for Recommendation

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-04T13:46:16.008038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:46:16.008038Z digest=sha256:60065d3e08b4cc937ec7b4a0ce0e3ba38a9bf48608baa320c479ba426c4cde60

Observation 90c40522-e7c8-41ed-8fa5-22d5e1360cec · inbound

Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization cites this paper.

Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization A Survey on Large Language Models for Recommendation

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-04T11:11:01.986317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T11:11:01.986317Z digest=sha256:1fa89ecf8d612644a4bd54b599970febb6216d11644258d1bb11f44d09ea2648

Observation 728aa95c-9f76-4d92-bb25-7512b3cb491a · inbound

UniRec: Unified Multimodal Encoding for LLM-Based Recommendations cites this paper.

UniRec: Unified Multimodal Encoding for LLM-Based Recommendations A Survey on Large Language Models for Recommendation

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-16T10:50:51.356517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-16T10:50:36.112197Z digest=sha256:23223740c4a6b755e61b06117fccbef27f92ca7daa3085f8cd8ee3a615e96fb5

Observation 77a3c461-2420-4c77-ac7c-c04602fd5f20 · inbound

Benchmark Leakage Trap: Can We Trust LLM-based Recommendation? cites this paper.

Benchmark Leakage Trap: Can We Trust LLM-based Recommendation? A Survey on Large Language Models for Recommendation

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-02T23:32:09.512965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T23:32:09.512965Z digest=sha256:d17ff318291873495475e3b1e790c786963a02110852a0ee459ec8bc5e7a29c4

Observation 8607b115-2736-4e66-bdfd-724b43f6d741 · inbound

Why Thinking Hurts: Diagnosing and Rectifying Linguistic Inertia in Large Language Models for Recommendation cites this paper.

Why Thinking Hurts: Diagnosing and Rectifying Linguistic Inertia in Large Language Models for Recommendation A Survey on Large Language Models for Recommendation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-02T22:31:36.948727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T22:31:36.948727Z digest=sha256:3bb1f8521cdaff78fd9db4f4303e85f9edc4530eeeb2aaa0994297a952aa7515

Observation 3d886cc6-badf-43d5-b8a3-fe47d1eb5438 · inbound

A Comparative Study of Demonstration Selection for Practical Large Language Models-based Next POI Prediction cites this paper.

A Comparative Study of Demonstration Selection for Practical Large Language Models-based Next POI Prediction A Survey on Large Language Models for Recommendation

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-15T11:15:30.124373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-15T11:12:59.755023Z digest=sha256:949f50b5f08a23ce84574638e5b5f14c6d7670f0af105e69af787489baecd3cd

Observation 5fdaf10f-1ba0-494f-b4af-e1f96bb7d985 · inbound

Diagnosing LLM-based Rerankers in Cold-Start Recommender Systems: Coverage, Exposure and Practical Mitigations cites this paper.

Diagnosing LLM-based Rerankers in Cold-Start Recommender Systems: Coverage, Exposure and Practical Mitigations A Survey on Large Language Models for Recommendation

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-16T05:27:23.191758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-16T05:23:49.538421Z digest=sha256:6a8d2451d42cb26f027916043a423ba37db6ae0de219dc34357699b55d2d90e1

Observation f0bd2b2b-d831-4038-9f94-029605fa4b1f · inbound

Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations cites this paper.

Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations A Survey on Large Language Models for Recommendation

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:06:04.903295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T04:09:10.125285Z digest=sha256:5b66dc75677f0914fb6448c4ed8cd079616afcadf6132de69ad3123f68446dba

Observation 69cbe4d4-ec10-46fb-9c5e-3f6f8a850bf3 · inbound

MATRAG: Multi-Agent Transparent Retrieval-Augmented Generation for Explainable Recommendations cites this paper.

MATRAG: Multi-Agent Transparent Retrieval-Augmented Generation for Explainable Recommendations A Survey on Large Language Models for Recommendation

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-16T06:10:40.822723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-16T06:07:51.567145Z digest=sha256:1d412708ee811d5909f1434957f9fb212694703900c02688bfc62dcb347264e2

Observation 392de1ae-97bf-4f4b-85ec-3d18ccbb9aa8 · inbound

Fortress: A Case Study in Stabilizing Search Recommendations via Temporal Data Augmentation and Feature Pruning cites this paper.

Fortress: A Case Study in Stabilizing Search Recommendations via Temporal Data Augmentation and Feature Pruning A Survey on Large Language Models for Recommendation

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-19T16:07:41.015365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-19T16:06:28.657109Z digest=sha256:4a09b121dadbc63ab6af0933485287342ad06d4b732b07656c031c0ceaff0264

Observation d188d485-0f91-4cbe-bc48-eea997b93337 · inbound

Ocean4Rec: Offline LLM-Derived OCEAN Profiles for Request-Time VOD Reranking cites this paper.

Ocean4Rec: Offline LLM-Derived OCEAN Profiles for Request-Time VOD Reranking A Survey on Large Language Models for Recommendation

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-06-30T15:34:48.762668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T15:15:52.806007Z digest=sha256:3aa8ffea41369ffc13c4cfa6074fd1950b03881cb119a40d0254598e9e16bbcf

Observation d44d8574-9887-454c-98a3-71bb2ab1cb71 · inbound

SafeGEO: Understanding Generative Engine Optimization Risks in Recommendation Agents cites this paper.

SafeGEO: Understanding Generative Engine Optimization Risks in Recommendation Agents A Survey on Large Language Models for Recommendation

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T11:34:38.171106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T11:26:25.931534Z digest=sha256:06a71f2c579c43edfc4df04eda3da66873d5332c2a67a2aa6bf449f07bfca763

Observation f75555b4-d5ec-4e43-b142-80ba8aa6e782 · inbound

ShopX: A Foundation Model for Intent-to-Item Fulfillment in Agentic Shopping cites this paper.

ShopX: A Foundation Model for Intent-to-Item Fulfillment in Agentic Shopping A Survey on Large Language Models for Recommendation

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-01T11:45:46.924261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-07-01T03:56:46.899707Z digest=sha256:4a025414c1dc7e9990ff91a16b450cf049bb434bd15a95a50f24952b64a85e8f

Observation 1d6a82e0-234a-4ec2-a517-14ba1f0ed432 · inbound

ShopX: A Foundation Model for Intent-to-Item Fulfillment in Agentic Shopping cites this paper.

ShopX: A Foundation Model for Intent-to-Item Fulfillment in Agentic Shopping A Survey on Large Language Models for Recommendation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-02T09:19:01.754575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T09:19:01.754575Z digest=sha256:87aa17847896ca12b438edc9551b87ae8ac15090c20850970897eb09e04c8e32

Observation 17e1d948-648a-43da-a565-e59cf06b7efe · inbound

Tokenizing Numerical and Embedding Features for LLM RecSys cites this paper.

Tokenizing Numerical and Embedding Features for LLM RecSys A Survey on Large Language Models for Recommendation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-02T07:26:30.514542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T07:26:30.514542Z digest=sha256:b571d25f844d99d14ee515d2941b193d735e40119da7cc4792dda8eda7351af0

Observation d357c7b8-ec05-4c20-b30d-a9a3b6071d06 · inbound

Tokenizing Numerical and Embedding Features for LLM RecSys cites this paper.

Tokenizing Numerical and Embedding Features for LLM RecSys A Survey on Large Language Models for Recommendation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-04T01:43:22.305241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T01:43:22.305241Z digest=sha256:aeb82f04857cc71dbed9b01859a08ded19538be726325ede574a6185a357c59b

Observation 522446a7-d248-4a0f-9283-3465f8988db7 · inbound

Bridging the Information Gap: Semantic Densification and Hindsight Distillation for Cold-Start Prediction cites this paper.

Bridging the Information Gap: Semantic Densification and Hindsight Distillation for Cold-Start Prediction A Survey on Large Language Models for Recommendation

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-01T19:13:16.607208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T19:13:16.607208Z digest=sha256:248a208736b8966f4ea630ce3aeb7051098e5d3de763382c45b96eb5057d1949

Observation 056f1ebf-7736-4f1f-89c4-939378ffaaf8 · inbound

LLM-Derived Priors for Thompson Sampling in Cold-Start Comment Recommendation cites this paper.

LLM-Derived Priors for Thompson Sampling in Cold-Start Comment Recommendation A Survey on Large Language Models for Recommendation

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-05T20:03:03.559299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:03:03.559299Z digest=sha256:1bf3a5528663a848100fea78e2124fd124f613342887130191ce92587fd6d488