9 citations · 17 across the 10 of their papers we have counts for
4 papers · 1 filter
Learning Query Encoders Can Be Hard Even When Vector Retrieval Is Geometrically Easy
Anders Wikum, Nina Mishra, Amin Saberi +1
Efficient vector retrieval requires both a corpus geometry that supports retrieving the right documents through vector similarity, and a query encoder that can embed queries near t…
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…
Distill to Detect: Exposing Stealth Biases in LLMs through Cartridge Distillation
Shayan Talaei, Abhinav Chinta, Devvrit Khatri +3
Language models deployed in high-stakes roles can potentially favor certain entities, brands, or viewpoints, steering user decisions at scale. Such preferential biases can be intro…
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…