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Paper Citation Record · LEDGER

Evaluating Large Language Models as Generative User Simulators for Conversational Recommendation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.09738.

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

pith.paper-citation-record.v1
2403.09738 v4

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 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:39:03.773227Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T17:28:02.561524Z

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 1394342d-548c-464a-95f7-9e837a41adac · inbound

A Survey on LLM-powered Agents for Recommender Systems cites this paper.

A Survey on LLM-powered Agents for Recommender Systems Evaluating Large Language Models as Generative User Simulators for Conversational Recommendation

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T19:39:03.773227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:39:03.773227Z digest=sha256:80786e921a641856cb87d02a8a575069da0ec5e0196f8b415e62532788721afe

Observation 62a4ed61-94b7-4149-b509-928b82e2af47 · inbound

CONFETTI: Conversational Function-Calling Evaluation Through Turn-Level Interactions cites this paper.

CONFETTI: Conversational Function-Calling Evaluation Through Turn-Level Interactions Evaluating Large Language Models as Generative User Simulators for Conversational Recommendation

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T11:36:38.601971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:36:38.601971Z digest=sha256:0e21906440e2997ba26e955e91d0351dbc3259094e6d13eaff16a5ca4d1e1982

Observation 7db04a51-54ee-4542-8586-b1491b43e33c · inbound

RecoWorld: Building Simulated Environments for Agentic Recommender Systems cites this paper.

RecoWorld: Building Simulated Environments for Agentic Recommender Systems Evaluating Large Language Models as Generative User Simulators for Conversational Recommendation

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-04T17:56:38.869320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T17:56:38.869320Z digest=sha256:837e2eb5ce5dcabad00ef2140dbd3eb51849c851ae973eb834bd44d9e4ce8e0c

Observation ac863992-6f07-4634-8d3c-9393ee090205 · inbound

Mind the Sim2Real Gap in User Simulation for Agentic Tasks cites this paper.

Mind the Sim2Real Gap in User Simulation for Agentic Tasks Evaluating Large Language Models as Generative User Simulators for Conversational Recommendation

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-04T05:51:29.358976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T05:51:29.358976Z digest=sha256:5d899d018769b1c9692472e0162e1216c72cd031d1a6204aa76b55cb9dd99033

Observation 951d67df-b2b8-4798-8972-b540732cfc64 · inbound

User Simulator-Guided Multi-Turn Preference Optimization for Reasoning LLM-based Conversational Recommendation cites this paper.

User Simulator-Guided Multi-Turn Preference Optimization for Reasoning LLM-based Conversational Recommendation Evaluating Large Language Models as Generative User Simulators for Conversational Recommendation

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:28:02.562737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T17:24:18.413112Z digest=sha256:7b233957394209f748f23939256c2aa825d5c99f00c003b255c1976802fd2589