3 papers
cs.IR2025
DTRec: Learning Dynamic Reasoning Trajectories for Sequential Recommendation
Yifan Shao, Peilin Zhou, Shoujin Wang +3
Inspired by advances in LLMs, reasoning-enhanced sequential recommendation performs multi-step deliberation before making final predictions, unlocking greater potential for capturi…
cs.IR2025
Intent-Guided Reasoning for Sequential Recommendation
Yifan Shao, Peilin Zhou
Sequential recommendation systems aim to capture users' evolving preferences from their interaction histories. Recent reasoningenhanced methods have shown promise by introducing de…
cs.IR2025
What Matters in LLM-Based Feature Extractor for Recommender? A Systematic Analysis of Prompts, Models, and Adaptation
Kainan Shi, Peilin Zhou, Ge Wang +2
Using Large Language Models (LLMs) to generate semantic features has been demonstrated as a powerful paradigm for enhancing Sequential Recommender Systems (SRS). This typically inv…