57 citations · 58 across the 3 of their papers we have counts for
5 papers
Learning to Diversify for Product Question Generation
Haggai Roitman, Uriel Singer, Yotam Eshel +2
We address the product question generation task. For a given product description, our goal is to generate questions that reflect potential user information needs that are either mi…
Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E-Commerce
Uriel Singer, Haggai Roitman, Yotam Eshel +5
In e-commerce, the watchlist enables users to track items over time and has emerged as a primary feature, playing an important role in users' shopping journey. Watchlist items typi…
Scheduled Multi-Task Learning: From Syntax to Translation
Eliyahu Kiperwasser, Miguel Ballesteros
Neural encoder-decoder models of machine translation have achieved impressive results, while learning linguistic knowledge of both the source and target languages in an implicit en…
Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations
Eliyahu Kiperwasser, Yoav Goldberg
We present a simple and effective scheme for dependency parsing which is based on bidirectional-LSTMs (BiLSTMs). Each sentence token is associated with a BiLSTM vector representing…
Easy-First Dependency Parsing with Hierarchical Tree LSTMs
Eliyahu Kiperwasser, Yoav Goldberg
We suggest a compositional vector representation of parse trees that relies on a recursive combination of recurrent-neural network encoders. To demonstrate its effectiveness, we us…