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Paper Citation Record · LEDGER

Leveraging Large Language Models for Pre-trained Recommender Systems

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2308.10837.

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

pith.paper-citation-record.v1
2308.10837 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:20:29.619885Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T21:06:50.722455Z

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 90a70fcc-2078-46d8-8621-1ff9294591eb · inbound

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models cites this paper.

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models Leveraging Large Language Models for Pre-trained Recommender Systems

Reference 78

Resolution
verified exact
arxiv_id, observed 2026-05-16T16:03:17.111574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-16T16:03:17.015913Z digest=sha256:1ad2daff462392f3b102cbc949f94747c79fb9353431716aabf04611f8fbb1a3

Observation cf2e8f94-19bb-4e35-a122-fc31b512c928 · inbound

ROMAS: A Role-Based Multi-Agent System for Database monitoring and Planning cites this paper.

ROMAS: A Role-Based Multi-Agent System for Database monitoring and Planning Leveraging Large Language Models for Pre-trained Recommender Systems

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T13:07:15.861225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:07:15.861225Z digest=sha256:528132beb63cbf4e82625aa972c08c3cd835f37406da1ba6b0ba217c91c60051

Observation 08ae441f-030c-4e19-b7ca-182ca0221df9 · inbound

Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs cites this paper.

Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs Leveraging Large Language Models for Pre-trained Recommender Systems

Reference 240

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T15:51:29.482869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-13T15:51:29.022336Z digest=sha256:b32ebc12538a9703b8292871404584c64f76198bcaf5ab36cbe8571c8d119b57

Observation 4f05e6d3-2817-4a36-bc8e-fd8611f7a282 · inbound

Cold-Start Recommendation towards the Era of Large Language Models (LLMs): A Comprehensive Survey and Roadmap cites this paper.

Cold-Start Recommendation towards the Era of Large Language Models (LLMs): A Comprehensive Survey and Roadmap Leveraging Large Language Models for Pre-trained Recommender Systems

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T22:17:37.609540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:17:37.609540Z digest=sha256:37c7e2fe093a9108f146acc57cc1982282cc00d7f23f914c33202e8310c18f88

Observation 0f9f4c89-c78f-4f88-ab98-165ecc8b2ed6 · 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 Leveraging Large Language Models for Pre-trained Recommender Systems

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T06:03:40.825462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:03:40.825462Z digest=sha256:a0b6c8dcec67ad8f7d955cb0d8261aa9638dab2d4fcf81b6c711fc012f113657

Observation b7ebcc83-d468-4123-b4bc-20f91b3d9ff4 · inbound

Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects cites this paper.

Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects Leveraging Large Language Models for Pre-trained Recommender Systems

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-15T19:20:29.619885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:20:29.619885Z digest=sha256:62b35a56370002a30191a0f353059c4e076bf31c1a3edce9dba53173200f74ae

Observation 0ebfb13f-9e03-4ab4-944e-edf9885d600e · inbound

Improving the Performance of Sequential Recommendation Systems with an Extended Large Language Model cites this paper.

Improving the Performance of Sequential Recommendation Systems with an Extended Large Language Model Leveraging Large Language Models for Pre-trained Recommender Systems

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T13:53:57.113945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:53:57.113945Z digest=sha256:27338fd48e656bf6e9e07759ee0ad0834a4080721e5396bce7b0495d10d0f824

Observation 6cfdaa3c-145e-4f2d-9bd8-baaf783018aa · inbound

Learning Decomposed Contextual Token Representations from Pretrained and Collaborative Signals for Generative Recommendation cites this paper.

Learning Decomposed Contextual Token Representations from Pretrained and Collaborative Signals for Generative Recommendation Leveraging Large Language Models for Pre-trained Recommender Systems

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-18T21:06:50.725426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-18T21:04:49.458441Z digest=sha256:595a6a13c5e262663f01d3c2ac2c3edb4625d8bf4a8f4bf485ae08a9349be010

Observation 698e79bd-2505-4d3c-af7c-cce126b45aa2 · inbound

A Survey on Generative Recommendation: Data, Model, and Tasks cites this paper.

A Survey on Generative Recommendation: Data, Model, and Tasks Leveraging Large Language Models for Pre-trained Recommender Systems

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-18T03:50:52.068473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T03:47:08.208082Z digest=sha256:8b8b9fc0b38e83879c4e27f3d5cc2e8691893d033edab8de890d9797b8068268

Observation 33894f8c-a1b6-489f-b6b4-30fe16403224 · inbound

TwiSTAR:Think Fast, Think Slow, Then Act,Generative Recommendation with Adaptive Reasoning cites this paper.

TwiSTAR:Think Fast, Think Slow, Then Act,Generative Recommendation with Adaptive Reasoning Leveraging Large Language Models for Pre-trained Recommender Systems

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:42:03.682286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-13T01:40:04.856714Z digest=sha256:759365e1a86a7c40a7e9207b7f71543309d4ea0ec5209f33d1463bd112fc1497

Observation 35e78f04-eb6a-4fda-beed-eb42ba79ac1f · inbound

Topology-Aware Tokenization for Generative Recommendation cites this paper.

Topology-Aware Tokenization for Generative Recommendation Leveraging Large Language Models for Pre-trained Recommender Systems

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-01T14:59:16.983921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:59:16.983921Z digest=sha256:cf881bd17c8d1538e32030cba0f6b72684ee0c6b53847fd354b7d8435f5e79ca