activity
20232026
most citedOptimizing Airbnb Search Journey with Multi-task Learning

15 citations · 15 across the 5 of their papers we have counts for

collaborators

5 papers

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

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…

cs.IR2026

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…

cs.LG2025

BiListing: Modality Alignment for Listings

Guillaume Guy, Mihajlo Grbovic, Chun How Tan +1

Airbnb is a leader in offering travel accommodations. Airbnb has historically relied on structured data to understand, rank, and recommend listings to guests due to the limited cap…

cs.IR2023★ 15 cited

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…