39 citations · 42 across the 8 of their papers we have counts for
8 papers
SelfDR: Self-Distillation from Reasoning for LLM-Based Recommendation
Chumeng Jiang, Jiayin Wang, Xinjie Lin +3
Large Language Models (LLMs) have recently emerged as powerful backbones for recommendation. To better elicit their capabilities, reasoning has been widely incorporated to help LLM…
Personalized Turn-Level User Conversation Satisfaction Benchmark
Zhefan Wang, Zhiqiang Guo, Weizhi Ma +3
User satisfaction with AI assistants is highly personalized: the same response may satisfy one user but disappoint another depending on what each user expects and what they have as…
CC-OR-Net: A Unified Framework for LTV Prediction through Structural Decoupling
Mingyu Zhao, Haoran Bai, Yu Tian +2
Customer Lifetime Value (LTV) prediction, a central problem in modern marketing, is characterized by a unique zero-inflated and long-tail data distribution. This distribution prese…
Open-Set Living Need Prediction with Large Language Models
Xiaochong Lan, Jie Feng, Yizhou Sun +5
Living needs are the needs people generate in their daily lives for survival and well-being. On life service platforms like Meituan, user purchases are driven by living needs, maki…
Enhancing ID-based Recommendation with Large Language Models
Lei Chen, Chen Gao, Xiaoyi Du +4
Large Language Models (LLMs) have recently garnered significant attention in various domains, including recommendation systems. Recent research leverages the capabilities of LLMs t…
NEON: Living Needs Prediction System in Meituan
Xiaochong Lan, Chen Gao, Shiqi Wen +6
Living needs refer to the various needs in human's daily lives for survival and well-being, including food, housing, entertainment, etc. On life service platforms that connect user…