collaborators

9 papers

cs.LG2026

Proximity Features: Privacy-Compliant Cold-Start Personalization at Airbnb

Wei Jiang, Bin Xu, Hui Gao +6

Personalization in two-sided marketplaces relies heavily on user-level features, yet for platforms with infrequent, high-consideration purchases, a large fraction of users lack suf…

cs.LG2026

JourneyFormer: Encoding Airbnb Guest Journey with Sequence Modeling

Daochen Zha, Chun How Tan, Xin Liu +9

Sequence modeling has become increasingly popular in recommendation and ranking algorithms, owing to its capacity to model users' historical behaviors and infer user intentions. De…

cs.IR2026

Bridging the Cold-Start Gap: LLM-Powered Synthetic Data Generation for Natural Language Search at Airbnb

Wendy Ran Wei, Hao Li, Weiwei Guo +9

Deploying natural language search systems presents a critical cold-start challenge: no real user queries to learn linguistic patterns, and no relevance labels to train ranking mode…

cs.IR2026

High Precision Audience Expansion via Extreme Classification in a Two-Sided Marketplace

Dillon Davis, Huiji Gao, Thomas Legrand +8

Airbnb search must balance a worldwide, highly varied supply of homes with guests whose location, amenity, style, and price expectations differ widely. Meeting those expectations h…

cs.IR2026

Applying Embedding-Based Retrieval to Airbnb Search

Mustafa Abdool, Soumyadip Banerjee, Moutupsi Paul +10

The goal of Airbnb search is to match guests with the ideal accommodation that fits their travel needs. This is a challenging problem, as popular search locations can have around a…

cs.IR2025

Learning to Comparison-Shop

Jie Tang, Daochen Zha, Xin Liu +4

In online marketplaces like Airbnb, users frequently engage in comparison shopping before making purchase decisions. Despite the prevalence of this behavior, a significant disconne…