2 citations · 2 across the 4 of their papers we have counts for
4 papers
DeepAffinity: Long-Term Aspect Preference Prediction in eCommerce using Small Language Models
Yotam Eshel, Guy Hadad, Guy Feigenblat +3
We explore predicting eCommerce user preferences for product aspects such as brand, size, and color - a task we define as Aspect Affinity. Solving this task improves customer under…
HotelQuEST: Balancing Quality and Efficiency in Agentic Search
Guy Hadad, Shadi Iskander, Oren Kalinsky +3
Agentic search has emerged as a promising paradigm for adaptive retrieval systems powered by large language models (LLMs). However, existing benchmarks primarily focus on quality,…
EncodeRec: An Embedding Backbone for Recommendation Systems
Guy Hadad, Neomi Rabaev, Bracha Shapira
Recent recommender systems increasingly leverage embeddings from large pre-trained language models (PLMs). However, such embeddings exhibit two key limitations: (1) PLMs are not ex…
X-Cross: Dynamic Integration of Language Models for Cross-Domain Sequential Recommendation
Guy Hadad, Haggai Roitman, Yotam Eshel +2
As new products are emerging daily, recommendation systems are required to quickly adapt to possible new domains without needing extensive retraining. This work presents ``X-Cross'…