3 papers
cs.IR2026
MCLMR: A Model-Agnostic Causal Learning Framework for Multi-Behavior Recommendation
Ranxu Zhang, Junjie Meng, Ying Sun +5
Multi-Behavior Recommendation (MBR) leverages multiple user interaction types (e.g., views, clicks, purchases) to enrich preference modeling and alleviate data sparsity issues in t…
cs.IR2026
Recommending Search Filters To Improve Conversions At Airbnb
Hao Li, Kedar Bellare, Siyu Yang +4
Airbnb, a two-sided online marketplace connecting guests and hosts, offers a diverse and unique inventory of accommodations, experiences, and services. Search filters play an impor…
cs.IR2025
Serendipitous Recommendation with Multimodal LLM
Haoting Wang, Jianling Wang, Hao Li +9
Conventional recommendation systems succeed in identifying relevant content but often fail to provide users with surprising or novel items. Multimodal Large Language Models (MLLMs)…