Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
May 12, 2024Open Access

A LLM-based Controllable, Scalable, Human-Involved User Simulator Framework for Conversational Recommender Systems

View Full Paper
Ask AI
Bookmark
Share

Authors

LZLixi ZhuBeijing Jiaotong UniversityXHXiaowen HuangBeijing Jiaotong UniversityJSJitao SangBeijing Jiaotong University

Discussion

Loading...

Member takes

Implication

Key Points

Key points are not available for this paper at this time.

Cite This Study

Zhu et al. (2024) studied this question.

synapsesocial.com/papers/68e6a879b6db64358762afbahttps://doi.org/10.48550/arxiv.2405.08035
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1How Reliable is Your Simulator? Analysis on the Limitations of Current LLM-based User Simulators for Conversational Recommendation2024 · 14 citations
  2. 2How Reliable is Your Simulator? Analysis on the Limitations of Current LLM-based User Simulators for Conversational Recommendation2024
  3. 3Do Mentioned Items Truly Matter? Enhancing Conversational Recommender Systems with Causal Intervention and Large Language Models2025 · 2 citations
  4. 4Limitations of Current Evaluation Practices for Conversational Recommender Systems and the Potential of User Simulation2025 · 6 citations
  5. 5MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models2024