Paper Citation Record · LEDGER

How Can Recommender Systems Benefit from Large Language Models: A Survey

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2306.05817.

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

pith.paper-citation-record.v1
2306.05817 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:03:43.553644Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T15:34:48.798253Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
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 2572aef2-445c-408f-a8c1-2c23a2ba9366 · inbound

A Survey on the Memory Mechanism of Large Language Model based Agents cites this paper.

A Survey on the Memory Mechanism of Large Language Model based Agents How Can Recommender Systems Benefit from Large Language Models: A Survey

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:21:39.830751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b7770e29-cc52-476c-b34d-2b03a1b3b900 · inbound

Optimizing Recall or Relevance? A Multi-Task Multi-Head Approach for Item-to-Item Retrieval in Recommendation cites this paper.

Optimizing Recall or Relevance? A Multi-Task Multi-Head Approach for Item-to-Item Retrieval in Recommendation How Can Recommender Systems Benefit from Large Language Models: A Survey

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T06:03:43.553644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ddd6889-3d65-4558-8c82-f90757c68a8e · inbound

LlamaRec-LKG-RAG: A Single-Pass, Learnable Knowledge Graph-RAG Framework for LLM-Based Ranking cites this paper.

LlamaRec-LKG-RAG: A Single-Pass, Learnable Knowledge Graph-RAG Framework for LLM-Based Ranking How Can Recommender Systems Benefit from Large Language Models: A Survey

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T05:40:12.634282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd13056c-ae68-464d-9041-459f1206fa49 · inbound

When Transformers Meet Recommenders: Integrating Self-Attentive Sequential Recommendation with Fine-Tuned LLMs cites this paper.

When Transformers Meet Recommenders: Integrating Self-Attentive Sequential Recommendation with Fine-Tuned LLMs How Can Recommender Systems Benefit from Large Language Models: A Survey

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T19:22:29.890345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9bb156e-7077-4a25-b77e-4046b99350b9 · inbound

Large Language Model-Enhanced Reinforcement Learning for Diverse and Novel Recommendations cites this paper.

Large Language Model-Enhanced Reinforcement Learning for Diverse and Novel Recommendations How Can Recommender Systems Benefit from Large Language Models: A Survey

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T13:06:32.425492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0b9944c-e6cc-4681-9854-eeccf7f37c99 · inbound

Not Just What, But When: Integrating Irregular Intervals to LLM for Sequential Recommendation cites this paper.

Not Just What, But When: Integrating Irregular Intervals to LLM for Sequential Recommendation How Can Recommender Systems Benefit from Large Language Models: A Survey

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T11:02:13.416000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95a048c5-68e5-46e1-9721-31a4df91d568 · inbound

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

Benchmark Leakage Trap: Can We Trust LLM-based Recommendation? How Can Recommender Systems Benefit from Large Language Models: A Survey

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T23:32:08.633592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d343495-a5ab-4a63-89a0-aa822fd993dc · 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 How Can Recommender Systems Benefit from Large Language Models: A Survey

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:34:48.799736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.