21 citations · 26 across the 10 of their papers we have counts for
9 papers · 1 filter
Improving and Evaluating the Detection of Fragmentation in News Recommendations with the Clustering of News Story Chains
Alessandra Polimeno, Myrthe Reuver, Sanne Vrijenhoek +1
News recommender systems play an increasingly influential role in shaping information access within democratic societies. However, tailoring recommendations to users' specific inte…
Dealing with Abbreviations in the Slovenian Biographical Lexicon
Angel Daza, Antske Fokkens, Tomaž Erjavec
Abbreviations present a significant challenge for NLP systems because they cause tokenization and out-of-vocabulary errors. They can also make the text less readable, especially in…
Perturbations and Subpopulations for Testing Robustness in Token-Based Argument Unit Recognition
Jonathan Kamp, Lisa Beinborn, Antske Fokkens
Argument Unit Recognition and Classification aims at identifying argument units from text and classifying them as pro or against. One of the design choices that need to be made whe…
Hate Speech Criteria: A Modular Approach to Task-Specific Hate Speech Definitions
Urja Khurana, Ivar Vermeulen, Eric Nalisnick +2
\textbf{Offensive Content Warning}: This paper contains offensive language only for providing examples that clarify this research and do not reflect the authors' opinions. Please b…
How Emotionally Stable is ALBERT? Testing Robustness with Stochastic Weight Averaging on a Sentiment Analysis Task
Urja Khurana, Eric Nalisnick, Antske Fokkens
Despite their success, modern language models are fragile. Even small changes in their training pipeline can lead to unexpected results. We study this phenomenon by examining the r…
Is Stance Detection Topic-Independent and Cross-topic Generalizable? -- A Reproduction Study
Myrthe Reuver, Suzan Verberne, Roser Morante +1
Cross-topic stance detection is the task to automatically detect stances (pro, against, or neutral) on unseen topics. We successfully reproduce state-of-the-art cross-topic stance…
Firearms and Tigers are Dangerous, Kitchen Knives and Zebras are Not: Testing whether Word Embeddings Can Tell
Pia Sommerauer, Antske Fokkens
This paper presents an approach for investigating the nature of semantic information captured by word embeddings. We propose a method that extends an existing human-elicited semant…
BiographyNet: Extracting Relations Between People and Events
Antske Fokkens, Serge ter Braake, Niels Ockeloen +4
This paper describes BiographyNet, a digital humanities project (2012-2016) that brings together researchers from history, computational linguistics and computer science. The proje…
Tackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency Parsing
Minh Le, Antske Fokkens
Error propagation is a common problem in NLP. Reinforcement learning explores erroneous states during training and can therefore be more robust when mistakes are made early in a pr…