b'Shay B. Cohen'

research

∙ 05/31/2023

Knowledge Base Question Answering for Space Debris Queries

Space agencies execute complex satellite operations that need to be supp...

0 Paul Darm, et al. ∙

research

∙ 05/26/2023

Sentence-Incremental Neural Coreference Resolution

We propose a sentence-incremental neural coreference resolution system w...

0 Matt Grenander, et al. ∙

research

∙ 05/24/2023

The Larger They Are, the Harder They Fail: Language Models do not Recognize Identifier Swaps in Python

Large Language Models (LLMs) have successfully been applied to code gene...

0 Antonio Valerio Miceli Barone, et al. ∙

research

∙ 05/23/2023

Detecting and Mitigating Hallucinations in Multilingual Summarisation

Hallucinations pose a significant challenge to the reliability of neural...

0 Yifu Qiu, et al. ∙

research

∙ 05/15/2023

PMIndiaSum: Multilingual and Cross-lingual Headline Summarization for Languages in India

This paper introduces PMIndiaSum, a new multilingual and massively paral...

0 Ashok Urlana, et al. ∙

research

∙ 02/21/2023

Causal Social Explanations for Stochastic Sequential Multi-Agent Decision-Making

We present a novel framework to generate causal explanations for the dec...

0 Balint Gyevnar, et al. ∙

research

∙ 02/18/2023

BERT is not The Count: Learning to Match Mathematical Statements with Proofs

We introduce a task consisting in matching a proof to a given mathematic...

0 Weixian Waylon Li, et al. ∙

research

∙ 11/17/2022

Abstractive Summarization Guided by Latent Hierarchical Document Structure

Sequential abstractive neural summarizers often do not use the underlyin...

0 Yifu Qiu, et al. ∙

research

∙ 10/22/2022

Understanding Domain Learning in Language Models Through Subpopulation Analysis

We investigate how different domains are encoded in modern neural networ...

0 Zheng Zhao, et al. ∙

research

∙ 06/17/2022

A Human-Centric Method for Generating Causal Explanations in Natural Language for Autonomous Vehicle Motion Planning

Inscrutable AI systems are difficult to trust, especially if they operat...

0 Balint Gyevnar, et al. ∙

research

∙ 05/25/2022

Factorizing Content and Budget Decisions in Abstractive Summarization of Long Documents by Sampling Summary Views

We argue that disentangling content selection from the budget used to co...

0 Marcio Fonseca, et al. ∙

research

∙ 05/20/2022

On the Trade-off between Redundancy and Local Coherence in Summarization

Extractive summarization systems are known to produce poorly coherent an...

0 Ronald Cardenas, et al. ∙

research

∙ 03/15/2022

Gold Doesn't Always Glitter: Spectral Removal of Linear and Nonlinear Guarded Attribute Information

We describe a simple and effective method (Spectral Attribute removaL; S...

0 Shun Shao, et al. ∙

research

∙ 10/05/2021

Co-training an Unsupervised Constituency Parser with Weak Supervision

We introduce a method for unsupervised parsing that relies on bootstrapp...

0 Nickil Maveli, et al. ∙

research

∙ 04/16/2021

Unsupervised Extractive Summarization by Human Memory Simulation

Summarization systems face the core challenge of identifying and selecti...

0 Ronald Cardenas, et al. ∙

research

∙ 02/03/2021

Learning to Match Mathematical Statements with Proofs

We introduce a novel task consisting in assigning a proof to a given mat...

0 Maximin Coavoux, et al. ∙

research

∙ 01/17/2021

Narration Generation for Cartoon Videos

Research on text generation from multimodal inputs has largely focused o...

0 Nikos Papasarantopoulos, et al. ∙

research

∙ 10/23/2020

A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing

Abstract Meaning Representations (AMR) are a broad-coverage semantic for...

7 Chunchuan Lyu, et al. ∙

research

∙ 10/09/2020

Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation

AMR-to-text generation is used to transduce Abstract Meaning Representat...

0 Yan Zhang, et al. ∙

research

∙ 09/28/2020

Reducing Quantity Hallucinations in Abstractive Summarization

It is well-known that abstractive summaries are subject to hallucination...

0 Zheng Zhao, et al. ∙

research

∙ 08/17/2020

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

We focus on learning a two-layer residual neural network with preactivat...

0 Zhunxuan Wang, et al. ∙

research

∙ 04/23/2020

Learning Dialog Policies from Weak Demonstrations

Deep reinforcement learning is a promising approach to training a dialog...

0 Gabriel Gordon-Hall, et al. ∙

research

∙ 09/07/2019

Semantic Role Labeling with Iterative Structure Refinement

Modern state-of-the-art Semantic Role Labeling (SRL) methods rely on exp...

0 Chunchuan Lyu, et al. ∙

research

∙ 07/19/2019

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

We introduce 'extreme summarization', a new single-document summarizatio...

0 Shashi Narayan, et al. ∙

research

∙ 04/21/2019

Obfuscation for Privacy-preserving Syntactic Parsing

The goal of homomorphic encryption is to encrypt data such that another ...

6 Zhifeng Hu, et al. ∙

research

∙ 04/03/2019

Jointly Extracting and Compressing Documents with Summary State Representations

We present a new neural model for text summarization that first extracts...

0 Afonso Mendes, et al. ∙

research

∙ 04/03/2019

Jointly Extracting and Compressing Documentswith Summary State Representations

We present a new neural model for text summarization that first extracts...

0 Afonso Mendes, et al. ∙

research

∙ 04/01/2019

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

We introduce a novel transition system for discontinuous constituency pa...

0 Maximin Coavoux, et al. ∙

research

∙ 03/27/2019

Structural Neural Encoders for AMR-to-text Generation

AMR-to-text generation is a problem recently introduced to the NLP commu...

0 Marco Damonte, et al. ∙

research

∙ 02/24/2019

Unlexicalized Transition-based Discontinuous Constituency Parsing

Lexicalized parsing models are based on the assumptions that (i) constit...

0 Maximin Coavoux, et al. ∙

research

∙ 09/03/2018

Multilingual Clustering of Streaming News

Clustering news across languages enables efficient media monitoring by a...

0 Sebastião Miranda, et al. ∙

research

∙ 08/28/2018

Privacy-preserving Neural Representations of Text

This article deals with adversarial attacks towards deep learning system...

0 Maximin Coavoux, et al. ∙

research

∙ 08/27/2018

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 ...

0 Shashi Narayan, et al. ∙

research

∙ 02/23/2018

Ranking Sentences for Extractive Summarization with Reinforcement Learning

Single document summarization is the task of producing a shorter version...

0 Shashi Narayan, et al. ∙

research

∙ 10/31/2017

Whodunnit? Crime Drama as a Case for Natural Language Understanding

In this paper we argue that crime drama exemplified in television progra...

0 Lea Frermann, et al. ∙

research

∙ 07/21/2017

Split and Rephrase

We propose a new sentence simplification task (Split-and-Rephrase) where...

0 Shashi Narayan, et al. ∙

research

∙ 04/14/2017

Cross-lingual Abstract Meaning Representation Parsing

Abstract Meaning Representation (AMR) annotation efforts have mostly foc...

0 Marco Damonte, et al. ∙

research

∙ 04/14/2017

Neural Extractive Summarization with Side Information

Most extractive summarization methods focus on the main body of the docu...

0 Shashi Narayan, et al. ∙

research

∙ 08/22/2016

An Incremental Parser for Abstract Meaning Representation

Meaning Representation (AMR) is a semantic representation for natural la...

0 Marco Damonte, et al. ∙

research

∙ 08/09/2016

Canonical Correlation Inference for Mapping Abstract Scenes to Text

We describe a technique for structured prediction, based on canonical co...

0 Nikos Papasarantopoulos, et al. ∙

research

∙ 06/07/2016

Optimizing Spectral Learning for Parsing

We describe a search algorithm for optimizing the number of latent state...

0 Shashi Narayan, et al. ∙

research

∙ 01/22/2016

Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing

One of the limitations of semantic parsing approaches to open-domain que...

0 Shashi Narayan, et al. ∙

research

∙ 09/03/2015

Encoding Prior Knowledge with Eigenword Embeddings

Canonical correlation analysis (CCA) is a method for reducing the dimens...

0 Dominique Osborne, et al. ∙

research

∙ 04/30/2015

Parsing Linear Context-Free Rewriting Systems with Fast Matrix Multiplication

We describe a matrix multiplication recognition algorithm for a subset o...

0 Shay B. Cohen, et al. ∙

research

∙ 06/28/2012

Elimination of Spurious Ambiguity in Transition-Based Dependency Parsing

We present a novel technique to remove spurious ambiguity from transitio...

0 Shay B. Cohen, et al. ∙

Shay B. Cohen

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