15 citations · 30 across the 15 of their papers we have counts for
13 papers · 1 filter
An Embarrassingly Simple Graph Heuristic Reveals Shortcut-Solvable Benchmarks for Sequential Recommendation
Haoyu Han, Li Ma, Hanbing Wang +9
Sequential recommendation has increasingly shifted toward generative recommenders that combine sequential patterns with semantic item information. Yet these methods are often evalu…
CASTLE: Contrastive and Seed-Guided Training for Cold-Start Natural Language Search
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…
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…
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…
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…
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…
Harnessing the Power of Interleaving and Counterfactual Evaluation for Airbnb Search Ranking
Qing Zhang, Alex Deng, Michelle Du +3
Evaluation plays a crucial role in the development of ranking algorithms on search and recommender systems. It enables online platforms to create user-friendly features that drive…
Beyond Pairwise Learning-To-Rank At Airbnb
Malay Haldar, Daochen Zha, Huiji Gao +2
There are three fundamental asks from a ranking algorithm: it should scale to handle a large number of items, sort items accurately by their utility, and impose a total order on th…
Transforming Location Retrieval at Airbnb: A Journey from Heuristics to Reinforcement Learning
Dillon Davis, Huiji Gao, Thomas Legrand +6
The Airbnb search system grapples with many unique challenges as it continues to evolve. We oversee a marketplace that is nuanced by geography, diversity of homes, and guests with…
Multi-objective Learning to Rank by Model Distillation
Jie Tang, Huiji Gao, Liwei He +1
In online marketplaces, search ranking's objective is not only to purchase or conversion (primary objective), but to also the purchase outcomes(secondary objectives), e.g. order ca…
Learning to Rank for Maps at Airbnb
Malay Haldar, Hongwei Zhang, Kedar Bellare +8
As a two-sided marketplace, Airbnb brings together hosts who own listings for rent with prospective guests from around the globe. Results from a guest's search for listings are dis…
Optimizing Airbnb Search Journey with Multi-task Learning
Chun How Tan, Austin Chan, Malay Haldar +6
At Airbnb, an online marketplace for stays and experiences, guests often spend weeks exploring and comparing multiple items before making a final reservation request. Each reservat…
Learning To Rank Diversely At Airbnb
Malay Haldar, Mustafa Abdool, Liwei He +3
Airbnb is a two-sided marketplace, bringing together hosts who own listings for rent, with prospective guests from around the globe. Applying neural network-based learning to rank…