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cs.AI2026
TRACE: Agentic Catalog Enrichment with Multi-source Evidence Grounding
Rohan Kumar, Steven Xu, Kyle MacDonald +4
Product catalogs underpin search, discovery, and recommendation in e-commerce, yet they are often attribute-sparse: the attributes shoppers and downstream systems rely on are eithe…
cs.AI2026
Decoupling Search from Reasoning: A Vendor-Agnostic Grounding Architecture for LLM Agents
Emmanuel Aboah Boateng, Kyle MacDonald, Amardeep Kumar +2
Production LLM agents increasingly depend on real-time search, yet native search grounding bundles retrieval policy, provider choice, evidence injection, cost, latency, and generat…
cs.AI2026
Agentic Multi-Source Grounding for Enhanced Query Intent Understanding: A DoorDash Case Study
Emmanuel Aboah Boateng, Kyle MacDonald, Akshad Viswanathan +1
Accurately mapping user queries to business categories is a fundamental Information Retrieval challenge for multi-category marketplaces, where context-sparse queries such as "Wildf…