Ivan Habernal | DeepAI

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Iryna Gurevych
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Lucie Flek
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∙ 07/13/2023

To share or not to share: What risks would laypeople accept to give sensitive data to differentially-private NLP systems?

Although the NLP community has adopted central differential privacy as a...

0 Christopher Weiss, et al. ∙

∙ 05/24/2023

Trade-Offs Between Fairness and Privacy in Language Modeling

Protecting privacy in contemporary NLP models is gaining in importance. ...

0 Cleo Matzken, et al. ∙

∙ 03/06/2023

Crowdsourcing on Sensitive Data with Privacy-Preserving Text Rewriting

Most tasks in NLP require labeled data. Data labeling is often done on c...

0 Nina Mouhammad, et al. ∙

∙ 02/15/2023

DP-BART for Privatized Text Rewriting under Local Differential Privacy

Privatized text rewriting with local differential privacy (LDP) is a rec...

0 Timour Igamberdiev, et al. ∙

∙ 11/05/2022

Privacy-Preserving Models for Legal Natural Language Processing

Pre-training large transformer models with in-domain data improves domai...

0 Ying Yin, et al. ∙

∙ 11/05/2022

The Legal Argument Reasoning Task in Civil Procedure

We present a new NLP task and dataset from the domain of the U.S. civil ...

0 Leonard Bongard, et al. ∙

∙ 09/05/2022

How Much User Context Do We Need? Privacy by Design in Mental Health NLP Application

Clinical NLP tasks such as mental health assessment from text, must take...

0 Ramit Sawhney, et al. ∙

∙ 08/22/2022

DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting

Text rewriting with differential privacy (DP) provides concrete theoreti...

0 Timour Igamberdiev, et al. ∙

∙ 08/12/2022

Mining Legal Arguments in Court Decisions

Identifying, classifying, and analyzing arguments in legal discourse has...

0 Ivan Habernal, et al. ∙

∙ 02/24/2022

How reparametrization trick broke differentially-private text representation learning

As privacy gains traction in the NLP community, researchers have started...

0 Ivan Habernal, et al. ∙

∙ 12/15/2021

One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks

Preserving privacy in training modern NLP models comes at a cost. We kno...

0 Manuel Senge, et al. ∙

∙ 09/07/2021

When differential privacy meets NLP: The devil is in the detail

Differential privacy provides a formal approach to privacy of individual...

0 Ivan Habernal, et al. ∙

∙ 02/10/2021

Privacy-Preserving Graph Convolutional Networks for Text Classification

Graph convolutional networks (GCNs) are a powerful architecture for repr...

0 Timour Igamberdiev, et al. ∙

∙ 10/07/2020

Why do you think that? Exploring Faithful Sentence-Level Rationales Without Supervision

Evaluating the trustworthiness of a model's prediction is essential for ...

0 Max Glockner, et al. ∙

∙ 02/19/2018

Before Name-calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation

Arguing without committing a fallacy is one of the main requirements of ...

0 Ivan Habernal, et al. ∙

∙ 08/04/2017

The Argument Reasoning Comprehension Task

Reasoning is a crucial part of natural language argumentation. In order ...

0 Ivan Habernal, et al. ∙

∙ 07/19/2017

Argotario: Computational Argumentation Meets Serious Games

An important skill in critical thinking and argumentation is the ability...

0 Ivan Habernal, et al. ∙

∙ 04/24/2017

What is the Essence of a Claim? Cross-Domain Claim Identification

Argument mining has become a popular research area in NLP. It typically ...

0 Johannes Daxenberger, et al. ∙

∙ 01/11/2016

Argumentation Mining in User-Generated Web Discourse

The goal of argumentation mining, an evolving research field in computat...

0 Ivan Habernal, et al. ∙

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