Author

Jia-Shu He

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#artificial intelligence Review Oct 2026

AgentPersonaBench: Benchmarking Persona-Driven User Simulation

We introduce AgentPersonaBench (APB), a benchmark evaluating whether persona conditioning faithfully steers downstream agent behavior. While language models are increasingly deployed for persona-driven user simulation, existing benchmarks primarily evaluate conversational styling or self-reports rather than authentic b...

Jin-Tao Huang, Yi-Fan Wang, Hong-Yuan Shen et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Safety as a Constraint: Fine-Tuning a LLM Recommender to Explain Itself

This paper trains a recommender LLM to generate personalized explanations for its reccomendation, based on the user's watching history at a large video streaming service, and concludes that an LLM-based recommender can be fine-tuned on other complex tasks without compromising its original recommendation performance.

Jia-Shu He, Emma Kong, J. Tan et al. · 0 citations