3 papers
cs.IR2026
MACS: A Hybrid Multi-Agent Framework for Reliable Conversational E-Commerce Recommendation
Juli Huang, Hannah Clay, Sajjad Beygi +3
Conversational recommendation for e-commerce is increasingly mediated by large language models (LLMs), yet many real-world deployments operate under a stricter requirement: recomme…
cs.IR2026
Offline RL for Adaptive Policy Retrieval in Prior Authorization
Ruslan Sharifullin, Maxim Gorshkov, Hannah Clay
Prior authorization (PA) requires interpretation of complex and fragmented coverage policies, yet existing retrieval-augmented systems rely on static top- strategies with fixed…
cs.AI2026
Entropy Guided Diversification and Preference Elicitation in Agentic Recommendation Systems
Dat Tran, Yongce Li, Hannah Clay +3
Users on e-commerce platforms can be uncertain about their preferences early in their search. Queries to recommendation systems are frequently ambiguous, incomplete, or weakly spec…