Customer Service
Customer service research focuses on improving efficiency and customer experience through technological advancements. Current efforts concentrate on developing and evaluating AI-powered solutions, such as chatbots utilizing architectures like BERT, LSTM, GPT, and reinforcement learning algorithms (DQN, DDQN), to automate tasks and enhance interactions. These models are being rigorously tested and refined using various metrics, including those assessing dialogue quality, emotion recognition, and task completion efficiency. The ultimate goal is to create more effective and personalized customer service systems, impacting both business operations and the customer journey.
Papers
Distributed Online Life-Long Learning (DOL3) for Multi-agent Trust and Reputation Assessment in E-commerce
Hariprasauth Ramamoorthy, Shubhankar Gupta, Suresh Sundaram
IGMaxHS -- An Incremental MaxSAT Solver with Support for XOR Clauses
Ole Lübke
Test-time Adaptation for Cross-modal Retrieval with Query Shift
Haobin Li, Peng Hu, Qianjun Zhang, Xi Peng, Xiting Liu, Mouxing Yang