Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A LLM-based Controllable, Scalable, Human-Involved User Simulator Framework for Conversational Recommender Systems
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2405.08035.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T19:39:03.936360Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T12:09:48.835062Z
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 3c76e7bd-0963-4da8-8539-71fa55834c47 · inbound
A Survey on LLM-powered Agents for Recommender Systems cites this paper.
A Survey on LLM-powered Agents for Recommender Systems A LLM-based Controllable, Scalable, Human-Involved User Simulator Framework for Conversational Recommender Systems
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T19:39:03.936360Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b4cfce8c-e134-4db8-a20d-f0e4aec05ec2 · inbound
RecUserSim: A Realistic and Diverse User Simulator for Evaluating Conversational Recommender Systems cites this paper.
RecUserSim: A Realistic and Diverse User Simulator for Evaluating Conversational Recommender Systems A LLM-based Controllable, Scalable, Human-Involved User Simulator Framework for Conversational Recommender Systems
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:57:05.469441Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e6247af0-36e5-4409-a14d-b6eaffe13a99 · inbound
Towards Fast Domain Adaptation and Fine-Grained User Simulation for Evaluating Conversational Recommender Systems cites this paper.
Towards Fast Domain Adaptation and Fine-Grained User Simulation for Evaluating Conversational Recommender Systems A LLM-based Controllable, Scalable, Human-Involved User Simulator Framework for Conversational Recommender Systems
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T12:09:48.836572Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f7a37788-e974-4ad6-bed9-2ff4a29118e2 · inbound
Attacking and Defending Multi-Agent Collaborative Filtering Systems Through Connectivity cites this paper.
Attacking and Defending Multi-Agent Collaborative Filtering Systems Through Connectivity A LLM-based Controllable, Scalable, Human-Involved User Simulator Framework for Conversational Recommender Systems
Reference 82
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:07:42.426490Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.