Re2LLM: Reflective Reinforcement Large Language Model for Session-based Recommendation

no code implementations • 25 Mar 2024 • Ziyan Wang, Yingpeng Du, Zhu Sun, Haoyan Chua, Kaidong Feng, Wenya Wang, Jie Zhang

However, the former methods struggle with optimal prompts to elicit the correct reasoning of LLMs due to the lack of task-specific feedback, leading to unsatisfactory recommendations.

Language Modelling Large Language Model +1

Dynamic In-Context Learning from Nearest Neighbors for Bundle Generation

no code implementations • 26 Dec 2023 • Zhu Sun, Kaidong Feng, Jie Yang, Xinghua Qu, Hui Fang, Yew-Soon Ong, Wenyuan Liu

To enhance reliability and mitigate the hallucination issue, we develop (1) a self-correction strategy to foster mutual improvement in both tasks without supervision signals; and (2) an auto-feedback mechanism to recurrently offer dynamic supervision based on the distinct mistakes made by ChatGPT on various neighbor sessions.

Hallucination In-Context Learning +2

Large Language Models for Intent-Driven Session Recommendations

1 code implementation • 7 Dec 2023 • Zhu Sun, Hongyang Liu, Xinghua Qu, Kaidong Feng, Yan Wang, Yew-Soon Ong

Intent-aware session recommendation (ISR) is pivotal in discerning user intents within sessions for precise predictions.