SPRec: Leveraging Self-Play to Debias Preference Alignment for Large Language Model-based Recommendations

C Gao, R Chen, S Yuan, K Huang, Y Yu… - arxiv preprint arxiv …, 2024 - arxiv.org
Large language models (LLMs) have attracted significant attention in recommendation
systems. Current LLM-based recommender systems primarily rely on supervised fine-tuning …

Large Language Models for Recommendation with Deliberative User Preference Alignment

Y Fang, W Wang, Y Zhang, F Zhu, Q Wang… - arxiv preprint arxiv …, 2025 - arxiv.org
While recent advancements in aligning Large Language Models (LLMs) with
recommendation tasks have shown great potential and promising performance overall …

Bidirectionally Guided Large Language Models for Consumer-Centric Personalized Recommendation

L Yu, P **ao, L Xu, S Kumari… - IEEE Transactions on …, 2025 - ieeexplore.ieee.org
With the increasing abundance of consumer electronics, consumers are facing the
challenge of information overload, making personalized recommendation systems (RSs) …

Toward High-Performance LLM Serving: A Simulation-Based Approach for Identifying Optimal Parallelism

YC Lin, W Kwon, R Pineda, FN Paravecino - arxiv preprint arxiv …, 2024 - arxiv.org
Serving Large Language Models (LLMs) efficiently has become crucial. LLMs are often
served with multiple devices using techniques like data, pipeline, and tensor parallelisms …

Recommender Systems in ambito medico: revisione sistematica e confronto pratico dei metodi di RS nei contesti clinici

G Michelazzi - 2024 - unire.unige.it
This thesis develops and evaluates a recommendation system (RS) for decision support in
healthcare, focusing on prioritizing laboratory tests using the MIMIC-IV dataset. Initially, a …