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Paper Citation Record · LEDGER

Leveraging Large Language Models for Pre-trained Recommender Systems

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 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 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:07:15.861225Z

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-16T16:03:17.015913Z digest=sha256:5d60349c9127cb83d1b9319c0138ab9f05a02bcd9230b5447d16814f4be217f8

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:cc83bc5414888bd391930de45a619344e38fd91cbc9206c886565e6754ead726

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-13T15:51:29.022336Z digest=sha256:57f6dca2da6bb2de19e7c9a1a27d57575989b257899081afdfee46c64511ff72

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=sha256:2c5ae9d1bb8675a81f6be7270d4a4110ccec489bba8a444623840217e6c1c315

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=sha256:5dab138b7f9410bf7428d7ea516643b2c460a7f8f60f2247ae80a592808c9966

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:ee52b03206e270d97d08d61791a7d8883fe5d3063fdd2371248972528d2e312c

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-18T21:04:49.458441Z digest=sha256:076ad3d9f8b766a981cf9aa7faeffe7dec1cf57db195625d1392b71d4258845f

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T03:47:08.208082Z digest=sha256:7edc2b72ba5576fee1427dae97027128787260f61ed3e90e9336ef349965ce4c

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-13T01:40:04.856714Z digest=sha256:2abe8f317b4b9193840e8727f36e79043f48af7626cc9c4474da201ecc17e741

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:bc31172fd811ddc614ac5b05ec163fde5cec5e7ab5d717917163c1793f6b7a73