6 papers
MedConsultBench: A Full-Cycle, Fine-Grained, Process-Aware Benchmark for Medical Consultation Agents
Chuhan Qiao, Jianghua Huang, Daxing Zhao +5
Current evaluations of medical consultation agents often prioritize outcome-oriented tasks, frequently overlooking the end-to-end process integrity and clinical safety essential fo…
AR-Med: Automated Relevance Enhancement in Medical Search via LLM-Driven Information Augmentation
Chuyue Wang, Jie Feng, Yuxi Wu +4
Accurate and reliable search on online healthcare platforms is critical for user safety and service efficacy. Traditional methods, however, often fail to comprehend complex and nua…
Bi-Level Decision-Focused Causal Learning for Large-Scale Marketing Optimization: Bridging Observational and Experimental Data
Shuli Zhang, Hao Zhou, Jiaqi Zheng +4
Online Internet platforms require sophisticated marketing strategies to optimize user retention and platform revenue -- a classical resource allocation problem. Traditional solutio…
Hidden Representation Clustering with Multi-Task Representation Learning towards Robust Online Budget Allocation
Xiaohan Wang, Yu Zhang, Guibin Jiang +2
Marketing optimization, commonly formulated as an online budget allocation problem, has emerged as a pivotal factor in driving user growth. Most existing research addresses this pr…
Decision Focused Causal Learning for Direct Counterfactual Marketing Optimization
Hao Zhou, Rongxiao Huang, Shaoming Li +4
Marketing optimization plays an important role to enhance user engagement in online Internet platforms. Existing studies usually formulate this problem as a budget allocation probl…
Interactive Ontology Matching with Cost-Efficient Learning
Bin Cheng, Jonathan Fürst, Tobias Jacobs +1
The creation of high-quality ontologies is crucial for data integration and knowledge-based reasoning, specifically in the context of the rising data economy. However, automatic on…