activity
20162023
most citedNeural Data-to-Text Generation Based on Small Datasets: Comparing the Added Value of Two Semi-Supervised Learning Approaches on Top of a Large Language Model

2 citations · 3 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CL2023

Native Language Identification with Big Bird Embeddings

Sergey Kramp, Giovanni Cassani, Chris Emmery

Native Language Identification (NLI) intends to classify an author's native language based on their writing in another language. Historically, the task has heavily relied on time-c…

cs.CL20231 cited

Tailoring Domain Adaptation for Machine Translation Quality Estimation

Javad Pourmostafa Roshan Sharami, Dimitar Shterionov, Frédéric Blain +4

While quality estimation (QE) can play an important role in the translation process, its effectiveness relies on the availability and quality of training data. For QE in particular…

cs.CL2023

User-Centered Security in Natural Language Processing

Chris Emmery

This dissertation proposes a framework of user-centered security in Natural Language Processing (NLP), and demonstrates how it can improve the accessibility of related research. Ac…

cs.CL20222 cited

Neural Data-to-Text Generation Based on Small Datasets: Comparing the Added Value of Two Semi-Supervised Learning Approaches on Top of a Large Language Model

Chris van der Lee, Thiago Castro Ferreira, Chris Emmery +2

This study discusses the effect of semi-supervised learning in combination with pretrained language models for data-to-text generation. It is not known whether semi-supervised lear…

cs.CL2022

Cyberbullying Classifiers are Sensitive to Model-Agnostic Perturbations

Chris Emmery, Ákos Kádár, Grzegorz Chrupała +1

A limited amount of studies investigates the role of model-agnostic adversarial behavior in toxic content classification. As toxicity classifiers predominantly rely on lexical cues…

cs.CL2021

NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender-Neutral Alternatives

Eva Vanmassenhove, Chris Emmery, Dimitar Shterionov

Recent years have seen an increasing need for gender-neutral and inclusive language. Within the field of NLP, there are various mono- and bilingual use cases where gender inclusive…