4 papers
SAGE: Sequence-level Adaptive Gradient Evolution for Generative Recommendation
Yu Xie, Xing Kai Ren, Ying Qi +1
Reinforcement learning-based preference optimization is increasingly used to align list-wise generative recommenders with complex, multi-objective user feedback, yet existing optim…
M2A: Multimodal Memory Agent with Dual-Layer Hybrid Memory for Long-Term Personalized Interactions
Junyu Feng, Binxiao Xu, Jiayi Chen +8
This work addresses the challenge of personalized question answering in long-term human-machine interactions: when conversational history spans weeks or months and exceeds the cont…
A Multi-Agent Conversational Bandit Approach to Online Evaluation and Selection of User-Aligned LLM Responses
Xiangxiang Dai, Yuejin Xie, Maoli Liu +4
Prompt-based offline methods are commonly used to optimize large language model (LLM) responses, but evaluating these responses is computationally intensive and often fails to acco…
RecLLM-R1: A Two-Stage Training Paradigm with Reinforcement Learning and Chain-of-Thought v1
Yu Xie, Xingkai Ren, Ying Qi +2
Traditional recommendation systems often grapple with "filter bubbles", underutilization of external knowledge, and a disconnect between model optimization and business policy iter…