9 citations · 9 across the 4 of their papers we have counts for
5 papers
Exploring Forum Post Retrieval with Generative Modeling
Yang Li, Yaguang Liu, Heng Liu +14
Generative recommendation (GR) has emerged as an alternative to embedding-based retrieval, building on the success of generative models in language and vision. We are exploring GR…
Modernizing Facebook Scoped Search: Keyword and Embedding Hybrid Retrieval with LLM Evaluation
Yongye Su, Zeya Zhang, Jane Kou +5
Beyond general web-scale search, social network search uniquely enables users to retrieve information and discover potential connections within their social context. We introduce a…
Semi-Supervised Clustering with Contrastive Learning for Discovering New Intents
Feng Wei, Zhenbo Chen, Zhenghong Hao +4
Most dialogue systems in real world rely on predefined intents and answers for QA service, so discovering potential intents from large corpus previously is really important for bui…
Semisupervised Learning on Heterogeneous Graphs and its Applications to Facebook News Feed
Cheng Ju, James Li, Bram Wasti +1
Graph-based semi-supervised learning is a fundamental machine learning problem, and has been well studied. Most studies focus on homogeneous networks (e.g. citation network, friend…
On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off
Kar Wai Lim, Scott Sanner, Shengbo Guo
It has been previously noted that optimization of the n-call@k relevance objective (i.e., a set-based objective that is 1 if at least n documents in a set of k are relevant, otherw…