4 citations · 4 across the 5 of their papers we have counts for
5 papers
AIGP: An LLM-Based Framework for Long-Term Value Alignment in E-Commerce Pricing
Chennan Ma, Yanning Zhang, Siqi Hong +3
Traditional dynamic pricing models in large-scale e-commerce suffer from limited interpretability, poor utilization of unstructured information, and misalignment with long-term bus…
Stagnant Neuron: Towards Understanding the Plasticity Loss in Multi-Agent Reinforcement Learning Value Factorization Methods
Zhengzhu Liu, Zeming Gao, Haoyuan Qin +7
Multi-Agent Reinforcement Learning (MARL) value factorization methods can suffer from a loss of plasticity, gradually failing to adapt when transferring to new task instances. We t…
LLM-as-a-Judge for Reliable and Explainable Offline Evaluation in Top-K Recommendation
Yue Que, Junyi Zhou, Xiaokun Zhang +3
Recommendation evaluation plays a crucial role in guiding the refinement and deployment of recommender systems. Most existing trials rely on offline evaluation using Top-K metrics…
PlanU: Large Language Model Reasoning through Planning under Uncertainty
Ziwei Deng, Mian Deng, Chenjing Liang +7
Large Language Models (LLMs) are increasingly being explored across a range of reasoning tasks. However, LLMs sometimes struggle with reasoning tasks under uncertainty that are rel…
RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization
Siqi Shen, Chennan Ma, Chao Li +5
Multi-agent systems are characterized by environmental uncertainty, varying policies of agents, and partial observability, which result in significant risks. In the context of Mult…