Shay B. Cohen

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Chancellor's fellow (assistant professor) at the University of Edinburgh (School of Informatics). Before that, he was a postdoctoral research scientist in the Department of Computer Science at Columbia University

Obfuscation for Privacy-preserving Syntactic Parsing

The goal of homomorphic encryption is to encrypt data such that another ...
04/21/2019 ∙ by Zhifeng Hu, et al. ∙ 6 ∙ share

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Elimination of Spurious Ambiguity in Transition-Based Dependency Parsing

We present a novel technique to remove spurious ambiguity from transitio...
06/28/2012 ∙ by Shay B. Cohen, et al. ∙ 0 ∙ share

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Whodunnit? Crime Drama as a Case for Natural Language Understanding

In this paper we argue that crime drama exemplified in television progra...
10/31/2017 ∙ by Lea Frermann, et al. ∙ 0 ∙ share

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Split and Rephrase

We propose a new sentence simplification task (Split-and-Rephrase) where...
07/21/2017 ∙ by Shashi Narayan, et al. ∙ 0 ∙ share

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Cross-lingual Abstract Meaning Representation Parsing

Abstract Meaning Representation (AMR) annotation efforts have mostly foc...
04/14/2017 ∙ by Marco Damonte, et al. ∙ 0 ∙ share

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Neural Extractive Summarization with Side Information

Most extractive summarization methods focus on the main body of the docu...
04/14/2017 ∙ by Shashi Narayan, et al. ∙ 0 ∙ share

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An Incremental Parser for Abstract Meaning Representation

Meaning Representation (AMR) is a semantic representation for natural la...
08/22/2016 ∙ by Marco Damonte, et al. ∙ 0 ∙ share

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Canonical Correlation Inference for Mapping Abstract Scenes to Text

We describe a technique for structured prediction, based on canonical co...
08/09/2016 ∙ by Nikos Papasarantopoulos, et al. ∙ 0 ∙ share

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Optimizing Spectral Learning for Parsing

We describe a search algorithm for optimizing the number of latent state...
06/07/2016 ∙ by Shashi Narayan, et al. ∙ 0 ∙ share

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Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing

One of the limitations of semantic parsing approaches to open-domain que...
01/22/2016 ∙ by Shashi Narayan, et al. ∙ 0 ∙ share

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Encoding Prior Knowledge with Eigenword Embeddings

Canonical correlation analysis (CCA) is a method for reducing the dimens...
09/03/2015 ∙ by Dominique Osborne, et al. ∙ 0 ∙ share

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Parsing Linear Context-Free Rewriting Systems with Fast Matrix Multiplication

We describe a matrix multiplication recognition algorithm for a subset o...
04/30/2015 ∙ by Shay B. Cohen, et al. ∙ 0 ∙ share

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Ranking Sentences for Extractive Summarization with Reinforcement Learning

Single document summarization is the task of producing a shorter version...
02/23/2018 ∙ by Shashi Narayan, et al. ∙ 0 ∙ share

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Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

We introduce extreme summarization, a new single-document summarization ...
08/27/2018 ∙ by Shashi Narayan, et al. ∙ 0 ∙ share

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Privacy-preserving Neural Representations of Text

This article deals with adversarial attacks towards deep learning system...
08/28/2018 ∙ by Maximin Coavoux, et al. ∙ 0 ∙ share

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Multilingual Clustering of Streaming News

Clustering news across languages enables efficient media monitoring by a...
09/03/2018 ∙ by Sebastião Miranda, et al. ∙ 0 ∙ share

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Unlexicalized Transition-based Discontinuous Constituency Parsing

Lexicalized parsing models are based on the assumptions that (i) constit...
02/24/2019 ∙ by Maximin Coavoux, et al. ∙ 0 ∙ share

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Jointly Extracting and Compressing Documentswith Summary State Representations

We present a new neural model for text summarization that first extracts...
04/03/2019 ∙ by Afonso Mendes, et al. ∙ 0 ∙ share

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Structural Neural Encoders for AMR-to-text Generation

AMR-to-text generation is a problem recently introduced to the NLP commu...
03/27/2019 ∙ by Marco Damonte, et al. ∙ 0 ∙ share

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Discontinuous Constituency Parsing with a Stack-Free Transition System and a Dynamic Oracle

We introduce a novel transition system for discontinuous constituency pa...
04/01/2019 ∙ by Maximin Coavoux, et al. ∙ 0 ∙ share

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Jointly Extracting and Compressing Documents with Summary State Representations

We present a new neural model for text summarization that first extracts...
04/03/2019 ∙ by Afonso Mendes, et al. ∙ 0 ∙ share

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What is this Article about? Extreme Summarization with Topic-aware Convolutional Neural Networks

We introduce 'extreme summarization', a new single-document summarizatio...
07/19/2019 ∙ by Shashi Narayan, et al. ∙ 0 ∙ share

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Semantic Role Labeling with Iterative Structure Refinement

Modern state-of-the-art Semantic Role Labeling (SRL) methods rely on exp...
09/07/2019 ∙ by Chunchuan Lyu, et al. ∙ 0 ∙ share

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Learning Dialog Policies from Weak Demonstrations

Deep reinforcement learning is a promising approach to training a dialog...
04/23/2020 ∙ by Gabriel Gordon-Hall, et al. ∙ 0 ∙ share

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Shay B. Cohen

Featured Co-authors

Mirella Lapata

Ivan Titov

Carlos Gómez-Rodríguez

André F. T. Martins

Daniel Gildea

Shashi Narayan

Siva Reddy

Claire Gardent

Zita Marinho

Guntis Barzdins

Marco Damonte

Obfuscation for Privacy-preserving Syntactic Parsing

Elimination of Spurious Ambiguity in Transition-Based Dependency Parsing

Whodunnit? Crime Drama as a Case for Natural Language Understanding

Split and Rephrase

Cross-lingual Abstract Meaning Representation Parsing

Neural Extractive Summarization with Side Information

An Incremental Parser for Abstract Meaning Representation

Canonical Correlation Inference for Mapping Abstract Scenes to Text

Optimizing Spectral Learning for Parsing

Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing

Encoding Prior Knowledge with Eigenword Embeddings

Parsing Linear Context-Free Rewriting Systems with Fast Matrix Multiplication

Ranking Sentences for Extractive Summarization with Reinforcement Learning

Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

Privacy-preserving Neural Representations of Text

Multilingual Clustering of Streaming News

Unlexicalized Transition-based Discontinuous Constituency Parsing

Jointly Extracting and Compressing Documentswith Summary State Representations

Structural Neural Encoders for AMR-to-text Generation

Discontinuous Constituency Parsing with a Stack-Free Transition System and a Dynamic Oracle

Jointly Extracting and Compressing Documents with Summary State Representations

What is this Article about? Extreme Summarization with Topic-aware Convolutional Neural Networks

Semantic Role Labeling with Iterative Structure Refinement

Learning Dialog Policies from Weak Demonstrations