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Paper Citation Record · LEDGER

SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2504.12722.

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

pith.paper-citation-record.v1
2504.12722 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:44:48.477482Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T14:05:46.445823Z

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 16aa5456-0da4-4f9f-8de7-48d5cc790b59 · inbound

GGBond: Growing Graph-Based AI-Agent Society for Socially-Aware Recommender Simulation cites this paper.

GGBond: Growing Graph-Based AI-Agent Society for Socially-Aware Recommender Simulation SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluation

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T13:44:48.477482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:44:48.477482Z digest=sha256:09a5396b285b8211b45e5d863b4bb4ec1d3bc739da3ba70110e85f3d4a77de7b

Observation de9bffd6-e94f-41e5-9f37-225aef9587a8 · inbound

CitySim: Modeling Urban Behaviors and City Dynamics with Large-Scale LLM-Driven Agent Simulation cites this paper.

CitySim: Modeling Urban Behaviors and City Dynamics with Large-Scale LLM-Driven Agent Simulation SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluation

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T22:22:39.583050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:22:39.583050Z digest=sha256:449151964201edd358db5ae3556999bebca664089bd47fb9b6f64d2cdcce6a54

Observation d1dcabc9-5295-41b1-a246-dfae46585eae · inbound

Exploration on Demand: From Algorithmic Control to User Empowerment cites this paper.

Exploration on Demand: From Algorithmic Control to User Empowerment SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluation

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-06T12:23:49.834842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:23:49.834842Z digest=sha256:2b9ac5f76e405e83de1fab0e04e708ded45abee315205ed21e1c63336cb25d7a

Observation 2ef140cf-f01d-463e-a8ff-8c14e27e3c0f · inbound

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

A Survey on Generative Recommendation: Data, Model, and Tasks SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluation

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-18T03:50:52.185463Z

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.

source=pdf_text observed=2026-05-18T03:47:08.208082Z digest=sha256:fc04393b181830edfd31bcce029f4cebd278679fea2595b3189e05cc2118045b

Observation e6abfce5-7142-4748-bdb0-e121432fafc3 · inbound

How Well Do Large Language Models Capture Human Personality? cites this paper.

How Well Do Large Language Models Capture Human Personality? SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluation

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:05:46.448183Z

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.

source=pdf_text observed=2026-06-30T22:20:10.160763Z digest=sha256:4d5a3a85a62f06c07dd4a1e3ec9783de03ec6e24af001fc54c10e5561deff81f