Shay B. Cohen

Discourse Representation Structure Parsing

2018

We introduce an open-domain neural semantic parser which generates formal meaning representations in the style of Discourse Representation Theory (DRT; Kamp and Reyle 1993). We propose a method which transforms Discourse Representation Structures (DRSs) to …

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

2018 · arXiv (Cornell University)

We introduce extreme summarization, a new single-document summarization task which does not favor extractive strategies and calls for an abstractive modeling approach. The idea is to create a short, one-sentence news summary answering the question …

Learning Two-Layer Residual Networks with Nonparametric Function Estimation by Convex Programming.

2020 · arXiv (Cornell University)

We focus on learning a two-layer residual neural network with preactivation by ReLU (preReLU-TLRN): Suppose the input $\mathbf{x}$ is from a distribution with support space $\mathbb{R}^d$ and the ground-truth generative model is a preReLU-TLRN, given …

Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing

2016 · Zenodo (CERN European Organization for Nuclear Research)

One of the limitations of semantic parsing approaches to open-domain question answering is the lexicosyntactic gap between natural language questions and knowledge base entries – there are many ways to ask a question, all with …

Are Large Language Model Temporally Grounded?

2024

Yifu Qiu, Zheng Zhao, Yftah Ziser, Anna Korhonen, Edoardo Ponti, Shay Cohen. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). …

Can Large Language Model Summarizers Adapt to Diverse Scientific Communication Goals?

2024

In this work, we investigate the controllability of large language models (LLMs) on scientific summarization tasks.We identify key stylistic and content coverage factors that characterize different types of summaries such as paper reviews, abstracts, and …

Unlexicalized Transition-based Discontinuous Constituency Parsing

2019 · Transactions of the Association for Computational Linguistics

Abstract Lexicalized parsing models are based on the assumptions that (i) constituents are organized around a lexical head and (ii) bilexical statistics are crucial to solve ambiguities. In this paper, we introduce an unlexicalized transition-based …

Structural Neural Encoders for

2019

Marco Damonte, Shay B. Cohen. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.

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

2019

Maximin Coavoux, Shay B. Cohen. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.

An Incremental Parser for Abstract Meaning Representation

2017

Meaning Representation (AMR) is a semantic representation for natural language that embeds annotations related to traditional tasks such as named entity recognition, semantic role labeling, word sense disambiguation and co-reference resolution. We describe a transition-based …