5 papers
Beyond Ranking Accuracy: Evaluating LLM-Cited Feature Rationales for Next Basket Repurchase Recommendation
Yanan Cao, Anay Dombe, Murali Mohana Krishna Dandu +5
Next-basket repurchase recommendation is commonly formulated as a ranking task: given a customer's purchase history, the system ranks previously purchased items that may be needed…
Timing-Aware Repurchase Prediction for Web-Scale E-Commerce: Survival Models for Multi-Surface Grocery Recommendation
Akshay Kekuda, Shreeranjani Srirangamsridharan, Ishan Bhatt +5
Repurchase recommenders in e-commerce are commonly framed as a binary question asking "will this customer buy this item within W days", a formulation that requires a separately tra…
CASE: Cadence-Aware Set Encoding for Large-Scale Next Basket Repurchase Recommendation
Yanan Cao, Ashish Ranjan, Sinduja Subramaniam +3
Repurchase behavior is a primary signal in large-scale retail recommendation, particularly in categories with frequent replenishment: many items in a user's next basket were previo…
Is More Context Always Better? Examining LLM Reasoning Capability for Time Interval Prediction
Yanan Cao, Farnaz Fallahi, Murali Mohana Krishna Dandu +9
Large Language Models (LLMs) have demonstrated impressive capabilities in reasoning and prediction across different domains. Yet, their ability to infer temporal regularities from…
S2SRec2: Set-to-Set Recommendation for Basket Completion with Recipe
Yanan Cao, Omid Memarrast, Shiqin Cai +3
In grocery e-commerce, customers often build ingredient baskets guided by dietary preferences but lack the expertise to create complete meals. Leveraging recipe knowledge to recomm…